Add topic review workflow and expansion tooling

Makefile

@@ -1,7 +1,7 @@
 PYTHONPATH_SRC=PYTHONPATH=src
 VENV_PYTHON=.venv/bin/python
 
-.PHONY: test test-live live-smoke
+.PHONY: test test-live live-smoke validate-talkorigins
 
 test:
 	$(PYTHONPATH_SRC) $(VENV_PYTHON) -m pytest -q
@@ -11,3 +11,6 @@ test-live:
 
 live-smoke:
 	CITEGEIST_SOURCE_CACHE=.cache/citegeist $(PYTHONPATH_SRC) $(VENV_PYTHON) scripts/live_smoke.py
+
+validate-talkorigins:
+	$(PYTHONPATH_SRC) $(VENV_PYTHON) -m citegeist validate-talkorigins talkorigins-out/talkorigins_manifest.json

README.md

@@ -46,12 +46,17 @@ The initial repo includes:
 - `pybtex`-backed BibTeX parsing and export in a repo-local virtual environment;
 - a SQLite-backed bibliography store;
 - a small CLI for ingest, search, inspection, and export;
-- review-state tracking on entries and per-field ingest provenance;
+- review-state tracking on entries, per-field ingest provenance, and field-level conflict review;
 - plaintext reference extraction into draft BibTeX for numbered, APA-like, wrapped-line, and simple book-style references;
-- identifier-first metadata resolution for DOI, OpenAlex, DBLP, and arXiv-backed entries, with OpenAlex title-search fallback;
+- identifier-first metadata resolution for DOI, OpenAlex, DBLP, arXiv, and DataCite-backed entries, with OpenAlex/DataCite title-search fallback;
 - local citation-graph traversal over stored `cites`, `cited_by`, and `crossref` edges;
 - Crossref- and OpenAlex-backed graph expansion that materializes draft related works and edge provenance;
 - a dedicated source-client layer with fixture/cache support for live-source development;
+- OAI-PMH Dublin Core harvesting for institutional repositories and thesis/dissertation sources;
+- OAI-PMH repository discovery via `Identify`, `ListSets`, and `ListMetadataFormats` to target harvests more precisely;
+- bibliography bootstrap workflows that can start from a seed `.bib`, a topic phrase, or both;
+- batch bootstrap orchestration from JSON job files containing seed BibTeX paths, topic phrases, or both;
+- a TalkOrigins scraper that fixes repeated-author plaintext references, emits per-topic seed BibTeX files, and writes a batch JSON specification;
 - normalized tables for entries, creators, identifiers, and citation relations;
 - full-text-search-ready indexing over title, abstract, and fulltext when SQLite FTS5 is available;
 - tests covering parsing, ingestion, relation storage, and search.
@@ -113,18 +118,107 @@ Or use the CLI directly:
 cd citegeist
 PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 ingest references.bib
 PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 search "semantic search"
-PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 show --provenance smith2024graphs
+PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 search "origin" --topic abiogenesis
+PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 show --provenance --conflicts smith2024graphs
 PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 set-status smith2024graphs reviewed
+PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 resolve-conflicts smith2024graphs title accepted
+PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 apply-conflict smith2024graphs title
+PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 bootstrap --seed-bib seed.bib --topic "bayesian nonparametrics"
+PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 bootstrap --topic "bayesian nonparametrics" --preview --topic-commit-limit 5
+PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 scrape-talkorigins talkorigins-out --limit-topics 5 --limit-entries-per-topic 20
 PYTHONPATH=src .venv/bin/python -m citegeist extract references.txt --output draft.bib
 PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 resolve smith2024graphs
+PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 topics
+PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 topic-entries abiogenesis
+PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 export-topic abiogenesis --output abiogenesis.bib
 PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 graph smith2024graphs --relation cites --depth 2 --missing-only
 PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 expand smith2024graphs --source crossref
 PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 expand smith2024graphs --source openalex --relation cited_by --limit 10
+PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 expand-topic abiogenesis --topic-phrase "abiogenesis origin chemistry" --source openalex --relation cites --seed-key seed2024 --min-relevance 0.3 --preview
+PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 set-topic-phrase abiogenesis "abiogenesis origin chemistry prebiotic"
+PYTHONPATH=src .venv/bin/python -m citegeist discover-oai https://example.edu/oai
+PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 harvest-oai https://example.edu/oai --metadata-prefix mods --from 2024-01-01 --until 2024-12-31 --limit 10
 PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 export --output reviewed.bib
 ```
 
 For live-source development, prefer fixture-backed or cache-backed source clients so resolver and expansion work can be exercised repeatedly without re-hitting upstream APIs on every run.
 
+For large legacy plaintext corpora such as the TalkOrigins bibliography, prefer a two-step workflow:
+
+1. `scrape-talkorigins` to generate cleaned per-topic `seed_bib` files plus a `talkorigins_jobs.json` batch spec.
+2. `bootstrap-batch` on that JSON file when you want to ingest, resolve, and expand from the generated seeds.
+
+The TalkOrigins scrape output now includes:
+
+- `seeds/*.bib` per-topic seed BibTeX files for `bootstrap-batch`
+- `plaintext/*.txt` per-topic cleaned GSA-style plaintext with repeated authors expanded
+- `site/topics/*.html` reconstructed topic pages with hide/show BibTeX blocks
+- `talkorigins_full.txt` and `talkorigins_full.bib` aggregate downloads
+- `snapshots/*.json` cached topic payloads so reruns can resume without re-fetching already scraped topics
+
+After a full scrape, run:
+
+```bash
+PYTHONPATH=src .venv/bin/python -m citegeist validate-talkorigins talkorigins-out/talkorigins_manifest.json
+PYTHONPATH=src .venv/bin/python -m citegeist duplicates-talkorigins talkorigins-out/talkorigins_manifest.json --limit 20
+PYTHONPATH=src .venv/bin/python -m citegeist duplicates-talkorigins talkorigins-out/talkorigins_manifest.json --limit 20 --preview --weak-only
+PYTHONPATH=src .venv/bin/python -m citegeist suggest-talkorigins-phrases talkorigins-out/talkorigins_manifest.json --output topic-phrases.json
+PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 stage-topic-phrases topic-phrases.json
+PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 review-topic-phrase abiogenesis accepted --notes "curated from local corpus"
+PYTHONPATH=src .venv/bin/python -m citegeist --db library.sqlite3 apply-topic-phrases topic-phrases.json
+PYTHONPATH=src .venv/bin/python -m citegeist --db talkorigins.sqlite3 enrich-talkorigins talkorigins-out/talkorigins_manifest.json --limit 20
+PYTHONPATH=src .venv/bin/python -m citegeist --db talkorigins-copy.sqlite3 enrich-talkorigins talkorigins-out/talkorigins_manifest.json --limit 5 --apply --allow-unsafe-search-matches
+PYTHONPATH=src .venv/bin/python -m citegeist --db talkorigins.sqlite3 review-talkorigins talkorigins-out/talkorigins_manifest.json --output talkorigins-review.json
+PYTHONPATH=src .venv/bin/python -m citegeist --db talkorigins.sqlite3 apply-talkorigins-corrections talkorigins-out/talkorigins_manifest.json talkorigins-corrections.json
+```
+
+That report summarizes parse coverage and flags suspicious entry-type / venue combinations for manual cleanup.
+It also reports duplicate clusters across topic seed files so you can gauge how much deduplication pressure to expect before ingestion.
+Use `duplicates-talkorigins` when you want to inspect specific clusters, filter by text, restrict the audit to one topic slug, or preview only weak canonicalization outcomes before importing.
+
+Use `suggest-talkorigins-phrases` to derive candidate stored expansion phrases from the existing TalkOrigins topic corpus itself. The output is deterministic JSON keyed by topic slug, with a suggested phrase plus the extracted keywords that drove it. This is a useful first pass before setting topic phrases in the database or editing generated batch jobs.
+
+Use `stage-topic-phrases` to load those suggestions into the database as review items. Staging stores the candidate in `suggested_phrase` and marks the topic `pending` without changing the active `expansion_phrase`.
+Use `review-topic-phrase` to accept or reject one staged suggestion in place. Accepting a suggestion copies it into `expansion_phrase`; rejecting it preserves the review state without changing the live phrase.
+Use `apply-topic-phrases` when you want a direct patch path instead of the staged review flow. It accepts either the raw suggestion list or an object with a `topics` list, and will apply `suggested_phrase` or `phrase` to matching topic slugs immediately.
+Use `enrich-talkorigins` when you want to target those weak canonical entries for resolver-based metadata upgrades before retrying graph expansion on imported topic slices.
+Use `review-talkorigins` when you want one JSON review artifact that combines weak canonical clusters with dry-run enrichment outcomes for manual cleanup.
+Use `expand-topic` when you already have both a topic phrase and a curated topic seed set in the database: it expands outward from the topic’s existing entries, then only assigns discovered works back to that topic if they clear a topic-relevance threshold. Write-enabled assignment is stricter than preview ranking: a candidate must clear the score threshold and show a non-generic title anchor to the topic phrase, so broad methods papers do not get attached just because their abstracts or related terms overlap. On large noisy topics, prefer `--seed-key` to restrict the run to just the trusted seed entries you want to expand from, and use `--preview` first to inspect discovered candidates and relevance scores before writing anything.
+
+Use `set-topic-phrase` to store a curated expansion phrase on the topic itself. When a stored phrase exists, `expand-topic` will use it automatically if you do not pass `--topic-phrase`. Batch bootstrap jobs can also set `topic_slug`, `topic_name`, and `topic_phrase` so curated topic metadata is created as part of the run.
+Use `topics --phrase-review-status pending` when you want to audit only topics whose staged phrase suggestions still need review.
+`--allow-unsafe-search-matches` exists only for bounded experiments on copied databases when you explicitly want to relax trust to exercise downstream expansion behavior.
+
+Correction files are simple JSON:
+
+```json
+{
+  "corrections": [
+    {
+      "key": "smith jane|1999|weak duplicate",
+      "entry_type": "article",
+      "review_status": "reviewed",
+      "fields": {
+        "journal": "Journal of Better Metadata",
+        "doi": "10.1000/weak",
+        "note": null
+      }
+    }
+  ]
+}
+```
+
+`fields` values overwrite the canonical entry for that duplicate-cluster key. Set a field to `null` to remove it.
+
+To import the reconstructed corpus into SQLite while collapsing duplicate works across topics into canonical entries:
+
+```bash
+PYTHONPATH=src .venv/bin/python -m citegeist --db talkorigins.sqlite3 ingest-talkorigins talkorigins-out/talkorigins_manifest.json
+```
+
+That import preserves many-to-many topic membership through the `topics` and `entry_topics` tables.
+After import, use `topics`, `topic-entries`, `search --topic`, and `export-topic` to inspect or export topic slices from the consolidated database.
+
 Live-source workflow:
 
 ```bash
@@ -147,7 +241,7 @@ make live-smoke
 
 ## Near-Term Priorities
 
-- additional resolvers and expansion paths for non-DOI scholarly ecosystems.
+- source adapters beyond OAI-PMH for additional non-DOI scholarly ecosystems.
 
 See [ROADMAP.md](./ROADMAP.md) for the prioritized phase plan and rationale.
 

src/citegeist/__init__.py

@@ -1,18 +1,52 @@
+from .batch import BatchBootstrapRunner, BatchJobResult, load_batch_jobs
 from .bibtex import BibEntry, parse_bibtex
+from .bootstrap import BootstrapResult, Bootstrapper
 from .expand import CrossrefExpander, OpenAlexExpander
 from .extract import extract_references
-from .resolve import MetadataResolver, merge_entries
+from .harvest import OaiMetadataFormat, OaiPmhHarvester, OaiSet
+from .resolve import MetadataResolver, merge_entries, merge_entries_with_conflicts
 from .sources import SourceClient
 from .storage import BibliographyStore
+from .talkorigins import (
+    TalkOriginsBatchExport,
+    TalkOriginsDuplicateCluster,
+    TalkOriginsEnrichmentResult,
+    TalkOriginsIngestReport,
+    TalkOriginsReviewExport,
+    TalkOriginsScraper,
+    TalkOriginsSeedSet,
+    TalkOriginsTopicPhraseSuggestion,
+    TalkOriginsTopic,
+    TalkOriginsValidationReport,
+)
 
 __all__ = [
     "BibEntry",
+    "BatchBootstrapRunner",
+    "BatchJobResult",
     "BibliographyStore",
+    "BootstrapResult",
+    "Bootstrapper",
     "CrossrefExpander",
     "MetadataResolver",
     "OpenAlexExpander",
+    "OaiPmhHarvester",
+    "OaiMetadataFormat",
+    "OaiSet",
     "SourceClient",
+    "TalkOriginsBatchExport",
+    "TalkOriginsDuplicateCluster",
+    "TalkOriginsEnrichmentResult",
+    "TalkOriginsIngestReport",
+    "TalkOriginsReviewExport",
+    "TalkOriginsScraper",
+    "TalkOriginsSeedSet",
+    "TalkOriginsTopicPhraseSuggestion",
+    "TalkOriginsTopic",
+    "TalkOriginsValidationReport",
     "extract_references",
+    "load_batch_jobs",
     "merge_entries",
+    "merge_entries_with_conflicts",
     "parse_bibtex",
 ]

src/citegeist/batch.py

@@ -0,0 +1,78 @@
+from __future__ import annotations
+
+import json
+from dataclasses import dataclass
+from pathlib import Path
+
+from .bootstrap import BootstrapResult, Bootstrapper
+from .storage import BibliographyStore
+
+
+@dataclass(slots=True)
+class BatchJobResult:
+    job_name: str
+    result_count: int
+    results: list[BootstrapResult]
+
+
+def load_batch_jobs(path: str | Path) -> list[dict]:
+    path = Path(path)
+    payload = json.loads(path.read_text(encoding="utf-8"))
+    if isinstance(payload, dict):
+        jobs = payload.get("jobs", [])
+    else:
+        jobs = payload
+    if not isinstance(jobs, list):
+        raise ValueError("Batch JSON must be a list of jobs or an object with a 'jobs' list")
+    normalized_jobs: list[dict] = []
+    for job in jobs:
+        if not isinstance(job, dict):
+            raise ValueError("Each batch job must be an object")
+        normalized = dict(job)
+        seed_bib = normalized.get("seed_bib")
+        if isinstance(seed_bib, str) and seed_bib:
+            seed_path = Path(seed_bib)
+            if not seed_path.is_absolute():
+                normalized["seed_bib"] = str((path.parent / seed_path).resolve())
+        normalized_jobs.append(normalized)
+    return normalized_jobs
+
+
+class BatchBootstrapRunner:
+    def __init__(self, bootstrapper: Bootstrapper | None = None) -> None:
+        self.bootstrapper = bootstrapper or Bootstrapper()
+
+    def run(self, store: BibliographyStore, jobs: list[dict]) -> list[BatchJobResult]:
+        results: list[BatchJobResult] = []
+        for index, job in enumerate(jobs, start=1):
+            seed_bib = job.get("seed_bib")
+            topic = job.get("topic")
+            topic_limit = int(job.get("topic_limit", 5))
+            topic_commit_limit = job.get("topic_commit_limit")
+            expand = bool(job.get("expand", True))
+            review_status = str(job.get("status", "draft"))
+            preview = bool(job.get("preview", False))
+            name = str(job.get("name") or f"job_{index}")
+            topic_slug = job.get("topic_slug")
+            topic_name = job.get("topic_name")
+            topic_phrase = job.get("topic_phrase")
+
+            seed_bibtex = None
+            if seed_bib:
+                seed_bibtex = Path(seed_bib).read_text(encoding="utf-8")
+
+            job_results = self.bootstrapper.bootstrap(
+                store,
+                seed_bibtex=seed_bibtex,
+                topic=topic,
+                topic_limit=topic_limit,
+                topic_commit_limit=int(topic_commit_limit) if topic_commit_limit is not None else None,
+                expand=expand,
+                review_status=review_status,
+                preview_only=preview,
+                topic_slug=str(topic_slug) if topic_slug else None,
+                topic_name=str(topic_name) if topic_name else None,
+                topic_phrase=str(topic_phrase) if topic_phrase else None,
+            )
+            results.append(BatchJobResult(name, len(job_results), job_results))
+        return results

src/citegeist/bibtex.py

@@ -5,8 +5,10 @@ from io import StringIO
 
 try:
     from pybtex.database import BibliographyData, Entry, Person, parse_string
+    from pybtex.bibtex.exceptions import BibTeXError
     from pybtex.database.output.bibtex import Writer
 except ImportError:  # pragma: no cover - exercised only outside the configured venv
+    BibTeXError = None
     BibliographyData = Entry = Person = Writer = None
     parse_string = None
 
@@ -40,7 +42,11 @@ def render_bibtex(entries: list[BibEntry]) -> str:
     _require_pybtex()
     bibliography_entries = {}
     for entry in entries:
-        fields = {key: value for key, value in entry.fields.items() if key not in {"author", "editor"}}
+        fields = {
+            key: _sanitize_bibtex_value(value)
+            for key, value in entry.fields.items()
+            if key not in {"author", "editor"}
+        }
         persons = {}
         for role in ("author", "editor"):
             raw_names = entry.fields.get(role)
@@ -49,7 +55,24 @@ def render_bibtex(entries: list[BibEntry]) -> str:
         bibliography_entries[entry.citation_key] = Entry(entry.entry_type, fields=fields, persons=persons)
 
     buffer = StringIO()
-    Writer().write_stream(BibliographyData(entries=bibliography_entries), buffer)
+    try:
+        Writer().write_stream(BibliographyData(entries=bibliography_entries), buffer)
+    except BibTeXError:
+        conservative_entries = {}
+        for entry in entries:
+            fields = {
+                key: _flatten_bibtex_braces(value)
+                for key, value in entry.fields.items()
+                if key not in {"author", "editor"}
+            }
+            persons = {}
+            for role in ("author", "editor"):
+                raw_names = entry.fields.get(role)
+                if raw_names:
+                    persons[role] = [Person(name.strip()) for name in raw_names.split(" and ") if name.strip()]
+            conservative_entries[entry.citation_key] = Entry(entry.entry_type, fields=fields, persons=persons)
+        buffer = StringIO()
+        Writer().write_stream(BibliographyData(entries=conservative_entries), buffer)
     return buffer.getvalue().strip()
 
 
@@ -58,3 +81,36 @@ def _require_pybtex() -> None:
         raise RuntimeError(
             "pybtex is required. Use the repo-local virtual environment under .venv/ for citegeist commands."
         )
+
+
+def _sanitize_bibtex_value(value: str) -> str:
+    depth = 0
+    parts: list[str] = []
+    for char in value:
+        if char == "{":
+            depth += 1
+            parts.append(char)
+            continue
+        if char == "}":
+            if depth == 0:
+                parts.append(")")
+            else:
+                depth -= 1
+                parts.append(char)
+            continue
+        parts.append(char)
+    if depth > 0:
+        open_count = depth
+        normalized = []
+        for char in parts:
+            if char == "{" and open_count > 0:
+                normalized.append("(")
+                open_count -= 1
+            else:
+                normalized.append(char)
+        return "".join(normalized)
+    return "".join(parts)
+
+
+def _flatten_bibtex_braces(value: str) -> str:
+    return value.replace("{", "(").replace("}", ")")

src/citegeist/bootstrap.py

@@ -0,0 +1,145 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+import re
+
+from .bibtex import BibEntry, parse_bibtex
+from .expand import CrossrefExpander, OpenAlexExpander
+from .resolve import MetadataResolver
+from .storage import BibliographyStore
+
+
+@dataclass(slots=True)
+class BootstrapResult:
+    citation_key: str
+    origin: str
+    created: bool
+    score: float = 0.0
+
+
+class Bootstrapper:
+    def __init__(
+        self,
+        resolver: MetadataResolver | None = None,
+        crossref_expander: CrossrefExpander | None = None,
+        openalex_expander: OpenAlexExpander | None = None,
+    ) -> None:
+        self.resolver = resolver or MetadataResolver()
+        self.crossref_expander = crossref_expander or CrossrefExpander(self.resolver)
+        self.openalex_expander = openalex_expander or OpenAlexExpander(self.resolver)
+
+    def bootstrap(
+        self,
+        store: BibliographyStore,
+        seed_bibtex: str | None = None,
+        topic: str | None = None,
+        topic_limit: int = 5,
+        topic_commit_limit: int | None = None,
+        expand: bool = True,
+        review_status: str = "draft",
+        preview_only: bool = False,
+        topic_slug: str | None = None,
+        topic_name: str | None = None,
+        topic_phrase: str | None = None,
+    ) -> list[BootstrapResult]:
+        results: list[BootstrapResult] = []
+        seed_keys: list[str] = []
+
+        if seed_bibtex:
+            for entry in parse_bibtex(seed_bibtex):
+                created = store.get_entry(entry.citation_key) is None
+                if not preview_only:
+                    store.upsert_entry(
+                        entry,
+                        raw_bibtex=None,
+                        source_type="bootstrap",
+                        source_label="seed_bibtex",
+                        review_status=review_status,
+                    )
+                    seed_keys.append(entry.citation_key)
+                results.append(BootstrapResult(entry.citation_key, "seed_bibtex", created))
+
+        if topic:
+            if not preview_only and (topic_slug or topic_name or topic_phrase):
+                store.ensure_topic(
+                    slug=topic_slug or _slugify(topic),
+                    name=topic_name or topic,
+                    source_type="bootstrap",
+                    expansion_phrase=topic_phrase or topic,
+                )
+            ranked_candidates = self._topic_candidates(topic, seed_keys, topic_limit)
+            if topic_commit_limit is not None:
+                ranked_candidates = ranked_candidates[:topic_commit_limit]
+
+            for entry, score in ranked_candidates:
+                created = store.get_entry(entry.citation_key) is None
+                if not preview_only:
+                    store.upsert_entry(
+                        entry,
+                        raw_bibtex=None,
+                        source_type="bootstrap",
+                        source_label=f"topic:{topic}",
+                        review_status=review_status,
+                    )
+                    seed_keys.append(entry.citation_key)
+                results.append(BootstrapResult(entry.citation_key, "topic", created, score=score))
+
+        if expand and not preview_only:
+            expanded_keys = list(dict.fromkeys(seed_keys))
+            for citation_key in expanded_keys:
+                for item in self.crossref_expander.expand_entry_references(store, citation_key):
+                    results.append(BootstrapResult(item.discovered_citation_key, "crossref_expand", item.created_entry))
+                for item in self.openalex_expander.expand_entry(store, citation_key, relation_type="cites", limit=topic_limit):
+                    results.append(BootstrapResult(item.discovered_citation_key, "openalex_expand", item.created_entry))
+
+        store.connection.commit()
+        return results
+
+    def _topic_candidates(self, topic: str, seed_keys: list[str], limit: int) -> list[tuple[BibEntry, float]]:
+        scored: dict[str, tuple[BibEntry, float]] = {}
+
+        for source_name, base_score, entries in (
+            ("openalex", 3.0, self.resolver.search_openalex(topic, limit=limit)),
+            ("crossref", 2.0, self.resolver.search_crossref(topic, limit=limit)),
+            ("datacite", 1.5, self.resolver.search_datacite(topic, limit=limit)),
+        ):
+            for entry in entries:
+                score = base_score + _topic_relevance_score(entry, topic) + _seed_overlap_score(entry, seed_keys)
+                existing = scored.get(entry.citation_key)
+                if existing is None or score > existing[1]:
+                    scored[entry.citation_key] = (entry, score)
+
+        ranked = sorted(
+            scored.values(),
+            key=lambda item: (-item[1], item[0].citation_key),
+        )
+        return ranked[:limit]
+
+
+def _topic_relevance_score(entry: BibEntry, topic: str) -> float:
+    topic_terms = _tokenize(topic)
+    title_terms = _tokenize(entry.fields.get("title", ""))
+    abstract_terms = _tokenize(entry.fields.get("abstract", ""))
+    overlap = len(topic_terms & (title_terms | abstract_terms))
+    return float(overlap)
+
+
+def _seed_overlap_score(entry: BibEntry, seed_keys: list[str]) -> float:
+    if not seed_keys:
+        return 0.0
+    title_terms = _tokenize(entry.fields.get("title", ""))
+    score = 0.0
+    for seed_key in seed_keys:
+        seed_terms = _tokenize(seed_key)
+        if seed_terms & title_terms:
+            score += 0.25
+    return score
+
+
+def _tokenize(value: str) -> set[str]:
+    return {token for token in re.split(r"\W+", value.lower()) if token}
+
+
+def _slugify(value: str) -> str:
+    slug = re.sub(r"[^a-z0-9]+", "-", value.lower()).strip("-")
+    return slug or "topic"

src/citegeist/expand.py

@@ -18,6 +18,20 @@ class ExpansionResult:
     source_label: str
 
 
+@dataclass(slots=True)
+class TopicExpansionResult:
+    topic_slug: str
+    source_citation_key: str
+    discovered_citation_key: str
+    discovered_title: str
+    created_entry: bool
+    relation_type: str
+    source_label: str
+    relevance_score: float
+    meets_relevance_threshold: bool
+    assigned_to_topic: bool
+
+
 class CrossrefExpander:
     def __init__(self, resolver: MetadataResolver | None = None) -> None:
         self.resolver = resolver or MetadataResolver()
@@ -163,6 +177,192 @@ class OpenAlexExpander:
         return _normalize_openalex_id(results[0].get("id", ""))
 
 
+class TopicExpander:
+    def __init__(
+        self,
+        crossref_expander: CrossrefExpander | None = None,
+        openalex_expander: OpenAlexExpander | None = None,
+    ) -> None:
+        self.crossref_expander = crossref_expander or CrossrefExpander()
+        self.openalex_expander = openalex_expander or OpenAlexExpander()
+
+    def expand_topic(
+        self,
+        store: BibliographyStore,
+        topic_slug: str,
+        topic_phrase: str | None = None,
+        source: str = "openalex",
+        relation_type: str = "cites",
+        seed_limit: int = 25,
+        per_seed_limit: int = 25,
+        min_relevance: float = 0.2,
+        seed_keys: list[str] | None = None,
+        preview_only: bool = False,
+    ) -> list[TopicExpansionResult]:
+        topic = store.get_topic(topic_slug)
+        if topic is None:
+            return []
+
+        phrase = (topic_phrase or str(topic.get("name") or topic_slug)).strip()
+        seeds = store.list_topic_entries(topic_slug, limit=seed_limit)
+        if seed_keys:
+            allowed = set(seed_keys)
+            seeds = [seed for seed in seeds if str(seed["citation_key"]) in allowed]
+        results: list[TopicExpansionResult] = []
+
+        for seed in seeds:
+            seed_key = str(seed["citation_key"])
+            if preview_only:
+                discovered_rows = self._preview_discoveries(
+                    store,
+                    seed_key,
+                    source=source,
+                    relation_type=relation_type,
+                    limit=per_seed_limit,
+                )
+            else:
+                discovered_rows = self._materialized_discoveries(
+                    store,
+                    seed_key,
+                    source=source,
+                    relation_type=relation_type,
+                    limit=per_seed_limit,
+                )
+
+            for row, target_entry in discovered_rows:
+                score = _topic_relevance_score(phrase, target_entry)
+                meets_threshold = _meets_topic_assignment_threshold(
+                    phrase,
+                    target_entry,
+                    min_relevance=min_relevance,
+                    relevance_score=score,
+                )
+                assigned = False
+                if not preview_only and meets_threshold and target_entry is not None:
+                    assigned = store.add_entry_topic(
+                        row.discovered_citation_key,
+                        topic_slug=topic_slug,
+                        topic_name=str(topic.get("name") or topic_slug),
+                        source_type="topic_expand",
+                        source_url=str(topic.get("source_url") or ""),
+                        source_label=f"{source}:{relation_type}:{seed_key}",
+                        confidence=score,
+                    )
+                results.append(
+                    TopicExpansionResult(
+                        topic_slug=topic_slug,
+                        source_citation_key=row.source_citation_key,
+                        discovered_citation_key=row.discovered_citation_key,
+                        discovered_title=str(target_entry.get("title") or ""),
+                        created_entry=row.created_entry,
+                        relation_type=row.relation_type,
+                        source_label=row.source_label,
+                        relevance_score=score,
+                        meets_relevance_threshold=meets_threshold,
+                        assigned_to_topic=assigned,
+                    )
+                )
+        store.connection.commit()
+        return results
+
+    def _materialized_discoveries(
+        self,
+        store: BibliographyStore,
+        citation_key: str,
+        source: str,
+        relation_type: str,
+        limit: int,
+    ) -> list[tuple[ExpansionResult, dict[str, object] | None]]:
+        if source == "crossref":
+            expansion_rows = self.crossref_expander.expand_entry_references(store, citation_key)
+        else:
+            expansion_rows = self.openalex_expander.expand_entry(
+                store,
+                citation_key,
+                relation_type=relation_type,
+                limit=limit,
+            )
+        return [(row, store.get_entry(row.discovered_citation_key)) for row in expansion_rows]
+
+    def _preview_discoveries(
+        self,
+        store: BibliographyStore,
+        citation_key: str,
+        source: str,
+        relation_type: str,
+        limit: int,
+    ) -> list[tuple[ExpansionResult, dict[str, object]]]:
+        if source == "crossref":
+            return self._preview_crossref_discoveries(store, citation_key, limit)
+        return self._preview_openalex_discoveries(store, citation_key, relation_type, limit)
+
+    def _preview_crossref_discoveries(
+        self,
+        store: BibliographyStore,
+        citation_key: str,
+        limit: int,
+    ) -> list[tuple[ExpansionResult, dict[str, object]]]:
+        entry = store.get_entry(citation_key)
+        if entry is None or not entry.get("doi"):
+            return []
+        doi = str(entry["doi"])
+        payload = self.crossref_expander.resolver.source_client.get_json(
+            f"https://api.crossref.org/works/{doi}?mailto=welsberr@gmail.com"
+        )
+        references = payload.get("message", {}).get("reference", [])[:limit]
+        rows: list[tuple[ExpansionResult, dict[str, object]]] = []
+        for index, reference in enumerate(references, start=1):
+            discovered = _crossref_reference_to_entry(reference, citation_key, index)
+            rows.append(
+                (
+                    ExpansionResult(
+                        source_citation_key=citation_key,
+                        discovered_citation_key=discovered.citation_key,
+                        created_entry=store.get_entry(discovered.citation_key) is None,
+                        relation_type="cites",
+                        source_label=f"crossref:references:{doi}",
+                    ),
+                    dict(discovered.fields),
+                )
+            )
+        return rows
+
+    def _preview_openalex_discoveries(
+        self,
+        store: BibliographyStore,
+        citation_key: str,
+        relation_type: str,
+        limit: int,
+    ) -> list[tuple[ExpansionResult, dict[str, object]]]:
+        entry = store.get_entry(citation_key)
+        if entry is None:
+            return []
+        openalex_id = entry.get("openalex") or self.openalex_expander._lookup_openalex_id(entry)
+        if not openalex_id:
+            return []
+        filter_name = "cited_by" if relation_type == "cites" else "cites"
+        query = urlencode({"filter": f"{filter_name}:{openalex_id}", "per-page": limit})
+        payload = self.openalex_expander.resolver.source_client.get_json(f"https://api.openalex.org/works?{query}")
+        works = payload.get("results", [])
+        rows: list[tuple[ExpansionResult, dict[str, object]]] = []
+        for work in works:
+            discovered = _openalex_work_to_entry(work)
+            source_key = citation_key if relation_type == "cites" else discovered.citation_key
+            rows.append(
+                (
+                    ExpansionResult(
+                        source_citation_key=source_key,
+                        discovered_citation_key=discovered.citation_key,
+                        created_entry=store.get_entry(discovered.citation_key) is None,
+                        relation_type=relation_type,
+                        source_label=f"openalex:{relation_type}:{openalex_id}",
+                    ),
+                    dict(discovered.fields),
+                )
+            )
+        return rows
+
+
 def _crossref_reference_to_entry(reference: dict, source_citation_key: str, ordinal: int) -> BibEntry:
     title = (
         reference.get("article-title")
@@ -211,6 +411,115 @@ def _normalize_text(value: str) -> str:
     return " ".join(value.split())
 
 
+def _topic_relevance_score(topic_phrase: str, entry: dict[str, object] | None) -> float:
+    if entry is None:
+        return 0.0
+    topic_terms = _expanded_keyword_terms(topic_phrase)
+    if not topic_terms:
+        return 0.0
+    title_terms = _expanded_keyword_terms(str(entry.get("title") or ""))
+    abstract_terms = _expanded_keyword_terms(str(entry.get("abstract") or ""))
+    keyword_terms = _expanded_keyword_terms(str(entry.get("keywords") or ""))
+    venue_terms = _expanded_keyword_terms(" ".join(str(entry.get(field) or "") for field in ("journal", "booktitle")))
+
+    score = 0.0
+    score += 0.6 * _term_overlap_ratio(topic_terms, title_terms)
+    score += 0.25 * _term_overlap_ratio(topic_terms, abstract_terms)
+    score += 0.1 * _term_overlap_ratio(topic_terms, keyword_terms)
+    score += 0.05 * _term_overlap_ratio(topic_terms, venue_terms)
+
+    phrase = _normalize_text(topic_phrase.casefold())
+    title = _normalize_text(str(entry.get("title") or "").casefold())
+    if phrase and title and phrase in title:
+        score = max(score, 0.75)
+
+    return min(score, 1.0)
+
+
+def _meets_topic_assignment_threshold(
+    topic_phrase: str,
+    entry: dict[str, object] | None,
+    min_relevance: float,
+    relevance_score: float | None = None,
+) -> bool:
+    if entry is None:
+        return False
+    score = relevance_score if relevance_score is not None else _topic_relevance_score(topic_phrase, entry)
+    if score < min_relevance:
+        return False
+    title_anchor = _title_topic_anchor_ratio(topic_phrase, str(entry.get("title") or ""))
+    return title_anchor >= 0.2
+
+
+def _keyword_terms(text: str) -> set[str]:
+    return {
+        _normalize_keyword(term)
+        for term in re.findall(r"[A-Za-z0-9]+", text.casefold())
+        if len(term) >= 4
+    }
+
+
+def _expanded_keyword_terms(text: str) -> set[str]:
+    terms = _keyword_terms(text)
+    expanded = set(terms)
+    for term in terms:
+        expanded.update(_related_topic_terms(term))
+    return expanded
+
+
+def _title_topic_anchor_ratio(topic_phrase: str, title: str) -> float:
+    normalized_phrase = _normalize_text(topic_phrase.casefold())
+    normalized_title = _normalize_text(title.casefold())
+    if normalized_phrase and normalized_title and normalized_phrase in normalized_title:
+        return 1.0
+
+    topic_terms = _core_topic_terms(topic_phrase)
+    title_terms = _keyword_terms(title)
+    if not topic_terms or not title_terms:
+        return 0.0
+    overlap = topic_terms & title_terms
+    if overlap:
+        return max(0.25, len(overlap) / len(topic_terms))
+    return 0.0
+
+
+def _core_topic_terms(topic_phrase: str) -> set[str]:
+    generic_terms = {"evolution", "origin", "origins", "science", "study", "studies"}
+    return {term for term in _keyword_terms(topic_phrase) if term not in generic_terms}
+
+
+def _term_overlap_ratio(topic_terms: set[str], candidate_terms: set[str]) -> float:
+    if not topic_terms or not candidate_terms:
+        return 0.0
+    return len(topic_terms & candidate_terms) / len(topic_terms)
+
+
+def _normalize_keyword(term: str) -> str:
+    normalized = term.casefold()
+    for suffix in ("isms", "ists", "ation", "ment", "ings", "ness", "isms", "ism", "ist", "ing", "ers", "er", "ies", "ied", "ed", "es", "s"):
+        if len(normalized) > len(suffix) + 3 and normalized.endswith(suffix):
+            if suffix in {"ies", "ied"}:
+                return normalized[: -len(suffix)] + "y"
+            return normalized[: -len(suffix)]
+    return normalized
+
+
+def _related_topic_terms(term: str) -> set[str]:
+    related_groups = (
+        {"human", "hominid", "hominin", "homo"},
+        {"chimpanzee", "chimp", "pan", "ape", "apes", "primate"},
+        {"primate", "primate", "ape", "apes", "hominid", "hominin"},
+        {"evolution", "evolutionary", "phylogeny", "phylogen", "ancestor", "ancestral"},
+        {"origin", "origins", "abiogenesis", "prebiotic"},
+        {"morphometry", "morphology", "cranial", "dental", "skeletal", "body"},
+        {"paleolithic", "paleoanthropology", "paleoanthropological", "pleistocene", "fossil"},
+    )
+    for group in related_groups:
+        if term in group:
+            return group - {term}
+    return set()
+
+
 def _openalex_work_to_entry(work: dict) -> BibEntry:
     title = _normalize_text(work.get("display_name", "") or "Untitled work")
     year = str(work.get("publication_year") or "")

src/citegeist/harvest.py

@@ -0,0 +1,317 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+from urllib.parse import urlencode
+import xml.etree.ElementTree as ET
+
+from .bibtex import BibEntry
+from .sources import SourceClient
+
+NS = {
+    "oai": "http://www.openarchives.org/OAI/2.0/",
+    "oai_dc": "http://www.openarchives.org/OAI/2.0/oai_dc/",
+    "dc": "http://purl.org/dc/elements/1.1/",
+    "mods": "http://www.loc.gov/mods/v3",
+}
+
+
+@dataclass(slots=True)
+class HarvestResult:
+    base_url: str
+    identifier: str
+    entry: BibEntry
+
+
+@dataclass(slots=True)
+class OaiSet:
+    set_spec: str
+    set_name: str
+    set_description: str = ""
+
+
+@dataclass(slots=True)
+class OaiMetadataFormat:
+    metadata_prefix: str
+    schema: str
+    metadata_namespace: str
+
+
+class OaiPmhHarvester:
+    def __init__(self, source_client: SourceClient | None = None) -> None:
+        self.source_client = source_client or SourceClient()
+
+    def identify(self, base_url: str) -> dict[str, str]:
+        root = self.source_client.get_xml(f"{base_url}?{urlencode({'verb': 'Identify'})}")
+        identify = root.find(".//oai:Identify", NS)
+        if identify is None:
+            return {}
+        payload: dict[str, str] = {}
+        for field_name in (
+            "repositoryName",
+            "baseURL",
+            "protocolVersion",
+            "adminEmail",
+            "earliestDatestamp",
+            "deletedRecord",
+            "granularity",
+        ):
+            payload[field_name] = _node_text(identify.find(f"oai:{field_name}", NS))
+        return payload
+
+    def list_sets(self, base_url: str) -> list[OaiSet]:
+        root = self.source_client.get_xml(f"{base_url}?{urlencode({'verb': 'ListSets'})}")
+        sets = root.findall(".//oai:set", NS)
+        results: list[OaiSet] = []
+        for node in sets:
+            results.append(
+                OaiSet(
+                    set_spec=_node_text(node.find("oai:setSpec", NS)),
+                    set_name=_node_text(node.find("oai:setName", NS)),
+                    set_description=_flatten_set_description(node.find("oai:setDescription", NS)),
+                )
+            )
+        return results
+
+    def list_metadata_formats(self, base_url: str, identifier: str | None = None) -> list[OaiMetadataFormat]:
+        params = {"verb": "ListMetadataFormats"}
+        if identifier:
+            params["identifier"] = identifier
+        root = self.source_client.get_xml(f"{base_url}?{urlencode(params)}")
+        formats = root.findall(".//oai:metadataFormat", NS)
+        results: list[OaiMetadataFormat] = []
+        for node in formats:
+            results.append(
+                OaiMetadataFormat(
+                    metadata_prefix=_node_text(node.find("oai:metadataPrefix", NS)),
+                    schema=_node_text(node.find("oai:schema", NS)),
+                    metadata_namespace=_node_text(node.find("oai:metadataNamespace", NS)),
+                )
+            )
+        return results
+
+    def list_records(
+        self,
+        base_url: str,
+        metadata_prefix: str = "oai_dc",
+        set_spec: str | None = None,
+        date_from: str | None = None,
+        date_until: str | None = None,
+        limit: int | None = None,
+    ) -> list[HarvestResult]:
+        results: list[HarvestResult] = []
+        params = {"verb": "ListRecords", "metadataPrefix": metadata_prefix}
+        if set_spec:
+            params["set"] = set_spec
+        if date_from:
+            params["from"] = date_from
+        if date_until:
+            params["until"] = date_until
+
+        ordinal = 1
+        next_url = f"{base_url}?{urlencode(params)}"
+        while next_url:
+            root = self.source_client.get_xml(next_url)
+            records = root.findall(".//oai:record", NS)
+            for record in records:
+                parsed = self._record_to_result(base_url, record, ordinal)
+                ordinal += 1
+                if parsed is not None:
+                    results.append(parsed)
+                if limit is not None and len(results) >= limit:
+                    return results
+            next_url = self._resumption_url(base_url, root)
+        return results
+
+    def get_record(
+        self,
+        base_url: str,
+        identifier: str,
+        metadata_prefix: str = "oai_dc",
+    ) -> HarvestResult | None:
+        params = {
+            "verb": "GetRecord",
+            "metadataPrefix": metadata_prefix,
+            "identifier": identifier,
+        }
+        root = self.source_client.get_xml(f"{base_url}?{urlencode(params)}")
+        record = root.find(".//oai:record", NS)
+        if record is None:
+            return None
+        return self._record_to_result(base_url, record, 1)
+
+    def _record_to_result(self, base_url: str, record: ET.Element, ordinal: int) -> HarvestResult | None:
+        identifier = _node_text(record.find("./oai:header/oai:identifier", NS))
+        metadata_node = record.find("./oai:metadata/*", NS)
+        if metadata_node is None or not identifier:
+            return None
+
+        entry = _metadata_node_to_entry(base_url, identifier, metadata_node, ordinal)
+        return HarvestResult(base_url=base_url, identifier=identifier, entry=entry)
+
+    def _resumption_url(self, base_url: str, root: ET.Element) -> str | None:
+        token = _node_text(root.find(".//oai:resumptionToken", NS))
+        if not token:
+            return None
+        return f"{base_url}?{urlencode({'verb': 'ListRecords', 'resumptionToken': token})}"
+
+
+def _oai_dc_to_entry(base_url: str, identifier: str, metadata: ET.Element, ordinal: int) -> BibEntry:
+    titles = _all_text(metadata.findall("dc:title", NS))
+    creators = _all_text(metadata.findall("dc:creator", NS))
+    dates = _all_text(metadata.findall("dc:date", NS))
+    descriptions = _all_text(metadata.findall("dc:description", NS))
+    identifiers = _all_text(metadata.findall("dc:identifier", NS))
+    publishers = _all_text(metadata.findall("dc:publisher", NS))
+    types = [value.lower() for value in _all_text(metadata.findall("dc:type", NS))]
+
+    title = titles[0] if titles else "Untitled record"
+    year = _first_year(dates)
+    entry_type = _guess_oai_entry_type(types)
+
+    fields: dict[str, str] = {
+        "title": title,
+        "oai": identifier,
+        "url": _best_identifier_url(identifiers) or f"{base_url}?verb=GetRecord&identifier={identifier}&metadataPrefix=oai_dc",
+        "note": "harvested_from = {oai_pmh}",
+    }
+    if creators:
+        fields["author"] = " and ".join(creators)
+    if year:
+        fields["year"] = year
+    if descriptions:
+        fields["abstract"] = descriptions[0]
+    if publishers:
+        fields["publisher"] = publishers[0]
+
+    citation_key = _oai_citation_key(creators, year, title, ordinal)
+    return BibEntry(entry_type=entry_type, citation_key=citation_key, fields=fields)
+
+
+def _mods_to_entry(base_url: str, identifier: str, metadata: ET.Element, ordinal: int) -> BibEntry:
+    title = _node_text(metadata.find(".//mods:titleInfo/mods:title", NS)) or "Untitled record"
+    sub_title = _node_text(metadata.find(".//mods:titleInfo/mods:subTitle", NS))
+    if sub_title:
+        title = f"{title}: {sub_title}"
+
+    creators: list[str] = []
+    for name in metadata.findall(".//mods:name", NS):
+        role_terms = [term.text or "" for term in name.findall(".//mods:roleTerm", NS)]
+        if role_terms and not any(term.lower() == "author" for term in role_terms):
+            continue
+        parts = [_node_text(part) for part in name.findall("./mods:namePart", NS)]
+        parts = [part for part in parts if part]
+        if parts:
+            creators.append(", ".join(parts) if len(parts) == 2 else " ".join(parts))
+
+    year = ""
+    for date_node in metadata.findall(".//mods:originInfo/mods:dateIssued", NS):
+        text = _node_text(date_node)
+        if len(text) >= 4 and text[:4].isdigit():
+            year = text[:4]
+            break
+
+    publisher = _node_text(metadata.find(".//mods:originInfo/mods:publisher", NS))
+    abstract = _node_text(metadata.find(".//mods:abstract", NS))
+    genre = _node_text(metadata.find(".//mods:genre", NS)).lower()
+    related_title = _node_text(metadata.find(".//mods:relatedItem/mods:titleInfo/mods:title", NS))
+    url = _node_text(metadata.find(".//mods:location/mods:url", NS))
+
+    entry_type = "phdthesis" if "thesis" in genre or "dissertation" in genre else "misc"
+    if not entry_type == "phdthesis":
+        if related_title:
+            entry_type = "article"
+
+    fields: dict[str, str] = {
+        "title": title,
+        "oai": identifier,
+        "url": url or f"{base_url}?verb=GetRecord&identifier={identifier}&metadataPrefix=mods",
+        "note": "harvested_from = {oai_pmh_mods}",
+    }
+    if creators:
+        fields["author"] = " and ".join(creators)
+    if year:
+        fields["year"] = year
+    if publisher:
+        fields["publisher"] = publisher
+    if abstract:
+        fields["abstract"] = abstract
+    if related_title:
+        fields["journal"] = related_title
+
+    citation_key = _oai_citation_key(creators, year, title, ordinal)
+    return BibEntry(entry_type=entry_type, citation_key=citation_key, fields=fields)
+
+
+def _metadata_node_to_entry(base_url: str, identifier: str, metadata: ET.Element, ordinal: int) -> BibEntry:
+    if metadata.tag.endswith("dc"):
+        return _oai_dc_to_entry(base_url, identifier, metadata, ordinal)
+    if metadata.tag.endswith("mods"):
+        return _mods_to_entry(base_url, identifier, metadata, ordinal)
+    return BibEntry(
+        entry_type="misc",
+        citation_key=_oai_citation_key([], "", identifier, ordinal),
+        fields={
+            "title": identifier,
+            "oai": identifier,
+            "url": f"{base_url}?verb=GetRecord&identifier={identifier}",
+            "note": f"unsupported_oai_metadata = {{{metadata.tag}}}",
+        },
+    )
+
+
+def _node_text(node: ET.Element | None) -> str:
+    if node is None or node.text is None:
+        return ""
+    return " ".join(node.text.split())
+
+
+def _all_text(nodes: list[ET.Element]) -> list[str]:
+    values = []
+    for node in nodes:
+        value = _node_text(node)
+        if value:
+            values.append(value)
+    return values
+
+
+def _first_year(dates: list[str]) -> str:
+    for date in dates:
+        if len(date) >= 4 and date[:4].isdigit():
+            return date[:4]
+    return ""
+
+
+def _guess_oai_entry_type(types: list[str]) -> str:
+    joined = " ".join(types)
+    if "thesis" in joined or "dissertation" in joined:
+        return "phdthesis"
+    if "article" in joined:
+        return "article"
+    if "book" in joined:
+        return "book"
+    return "misc"
+
+
+def _best_identifier_url(identifiers: list[str]) -> str:
+    for identifier in identifiers:
+        if identifier.startswith("http://") or identifier.startswith("https://"):
+            return identifier
+    return ""
+
+
+def _oai_citation_key(creators: list[str], year: str, title: str, ordinal: int) -> str:
+    author = creators[0] if creators else "oai"
+    family = author.split(",")[0] if "," in author else author.split()[-1]
+    family = "".join(ch for ch in family.lower() if ch.isalnum()) or "oai"
+    first_word = "".join(ch for ch in title.split()[0].lower() if ch.isalnum()) if title.split() else "untitled"
+    return f"{family}{year or 'nd'}{first_word}{ordinal}"
+
+
+def _flatten_set_description(node: ET.Element | None) -> str:
+    if node is None:
+        return ""
+    parts = []
+    for child in node.iter():
+        if child.text and child.text.strip():
+            parts.append(" ".join(child.text.split()))
+    return " ".join(parts)

src/citegeist/resolve.py

@@ -30,6 +30,9 @@ class MetadataResolver:
             resolved = self.resolve_doi(doi)
             if resolved is not None:
                 return resolved
+            resolved = self.resolve_datacite_doi(doi)
+            if resolved is not None:
+                return resolved
 
         if openalex_id := entry.fields.get("openalex"):
             resolved = self.resolve_openalex(openalex_id)
@@ -47,6 +50,20 @@ class MetadataResolver:
                 return resolved
 
         if title := entry.fields.get("title"):
+            resolved = self.search_crossref_best_match(
+                title=title,
+                author_text=entry.fields.get("author", ""),
+                year=entry.fields.get("year", ""),
+            )
+            if resolved is not None:
+                return resolved
+            resolved = self.search_datacite_best_match(
+                title=title,
+                author_text=entry.fields.get("author", ""),
+                year=entry.fields.get("year", ""),
+            )
+            if resolved is not None:
+                return resolved
             resolved = self.search_openalex_best_match(
                 title=title,
                 author_text=entry.fields.get("author", ""),
@@ -75,6 +92,26 @@ class MetadataResolver:
         items = payload.get("message", {}).get("items", [])
         return [_crossref_message_to_entry(item) for item in items]
 
+    def search_crossref_best_match(
+        self,
+        title: str,
+        author_text: str = "",
+        year: str = "",
+    ) -> Resolution | None:
+        candidate = _select_best_title_match(
+            self.search_crossref(title, limit=5),
+            title=title,
+            author_text=author_text,
+            year=year,
+        )
+        if candidate is None:
+            return None
+        return Resolution(
+            entry=candidate,
+            source_type="resolver",
+            source_label=f"crossref:search:{title}",
+        )
+
     def resolve_dblp(self, dblp_key: str) -> Resolution | None:
         encoded_key = urllib.parse.quote(dblp_key, safe="/:")
         text = self.source_client.get_text(f"https://dblp.org/rec/{encoded_key}.bib")
@@ -128,6 +165,43 @@ class MetadataResolver:
             source_label=f"openalex:id:{normalized_id}",
         )
 
+    def resolve_datacite_doi(self, doi: str) -> Resolution | None:
+        encoded = urllib.parse.quote(doi, safe="")
+        payload = self.source_client.get_json(f"https://api.datacite.org/dois/{encoded}")
+        data = payload.get("data", {})
+        if not data:
+            return None
+        return Resolution(
+            entry=_datacite_work_to_entry(data),
+            source_type="resolver",
+            source_label=f"datacite:doi:{doi}",
+        )
+
+    def search_datacite(self, title: str, limit: int = 5) -> list[BibEntry]:
+        query = urllib.parse.urlencode({"query": title, "page[size]": limit})
+        payload = self.source_client.get_json(f"https://api.datacite.org/dois?{query}")
+        return [_datacite_work_to_entry(item) for item in payload.get("data", [])]
+
+    def search_datacite_best_match(
+        self,
+        title: str,
+        author_text: str = "",
+        year: str = "",
+    ) -> Resolution | None:
+        candidate = _select_best_title_match(
+            self.search_datacite(title, limit=5),
+            title=title,
+            author_text=author_text,
+            year=year,
+        )
+        if candidate is None:
+            return None
+        return Resolution(
+            entry=candidate,
+            source_type="resolver",
+            source_label=f"datacite:search:{title}",
+        )
+
     def search_openalex(self, title: str, limit: int = 5) -> list[BibEntry]:
         query = urllib.parse.urlencode({"search": title, "per-page": limit})
         payload = self.source_client.get_json(f"https://api.openalex.org/works?{query}")
@@ -139,42 +213,50 @@ class MetadataResolver:
         author_text: str = "",
         year: str = "",
     ) -> Resolution | None:
-        candidates = self.search_openalex(title, limit=5)
+        candidate = _select_best_title_match(
-        if not candidates:
+            self.search_openalex(title, limit=5),
+            title=title,
+            author_text=author_text,
+            year=year,
+        )
+        if candidate is None:
             return None
-
-        title_norm = _normalize_match_text(title)
-        author_norm = _normalize_match_text(author_text)
-        for candidate in candidates:
-            candidate_title = _normalize_match_text(candidate.fields.get("title", ""))
-            candidate_author = _normalize_match_text(candidate.fields.get("author", ""))
-            candidate_year = candidate.fields.get("year", "")
-            if candidate_title == title_norm:
-                if author_norm and candidate_author and author_norm.split(" and ")[0] not in candidate_author:
-                    continue
-                if year and candidate_year and year != candidate_year:
-                    continue
-                return Resolution(
-                    entry=candidate,
-                    source_type="resolver",
-                    source_label=f"openalex:search:{title}",
-                )
-
         return Resolution(
-            entry=candidates[0],
+            entry=candidate,
             source_type="resolver",
             source_label=f"openalex:search:{title}",
         )
 
 def merge_entries(base: BibEntry, resolved: BibEntry) -> BibEntry:
+    merged, _ = merge_entries_with_conflicts(base, resolved)
+    return merged
+
+
+def merge_entries_with_conflicts(base: BibEntry, resolved: BibEntry) -> tuple[BibEntry, list[dict[str, str]]]:
     merged_fields = dict(base.fields)
+    conflicts: list[dict[str, str]] = []
     for key, value in resolved.fields.items():
-        if value and (key not in merged_fields or not merged_fields[key]):
+        if not value:
+            continue
+        current_value = merged_fields.get(key, "")
+        if current_value and current_value != value:
+            conflicts.append(
+                {
+                    "field_name": key,
+                    "current_value": current_value,
+                    "proposed_value": value,
+                }
+            )
+            continue
+        if key not in merged_fields or not merged_fields[key]:
             merged_fields[key] = value
-    return BibEntry(
+    return (
-        entry_type=base.entry_type or resolved.entry_type,
+        BibEntry(
-        citation_key=base.citation_key,
+            entry_type=base.entry_type or resolved.entry_type,
-        fields=merged_fields,
+            citation_key=base.citation_key,
+            fields=merged_fields,
+        ),
+        conflicts,
     )
 
 
@@ -363,3 +445,123 @@ def _normalize_match_text(value: str) -> str:
     lowered = value.lower()
     lowered = re.sub(r"\W+", " ", lowered)
     return " ".join(lowered.split())
+
+
+def _select_best_title_match(
+    candidates: list[BibEntry],
+    title: str,
+    author_text: str = "",
+    year: str = "",
+) -> BibEntry | None:
+    if not candidates:
+        return None
+
+    title_norm = _normalize_match_text(title)
+    author_tokens = _author_match_tokens(author_text)
+    year_text = str(year or "").strip()
+
+    for candidate in candidates:
+        candidate_title = _normalize_match_text(candidate.fields.get("title", ""))
+        if candidate_title != title_norm:
+            continue
+        candidate_year = str(candidate.fields.get("year", "") or "").strip()
+        if year_text and candidate_year and year_text != candidate_year:
+            continue
+        if author_tokens and not _candidate_matches_author_tokens(candidate, author_tokens):
+            continue
+        return candidate
+    return None
+
+
+def _author_match_tokens(author_text: str) -> set[str]:
+    normalized = _normalize_match_text(author_text)
+    if not normalized:
+        return set()
+    tokens = {
+        token
+        for token in re.findall(r"[a-z0-9]+", normalized)
+        if len(token) >= 2 and token not in {"and", "et", "al"}
+    }
+    return tokens
+
+
+def _candidate_matches_author_tokens(candidate: BibEntry, author_tokens: set[str]) -> bool:
+    candidate_author = _normalize_match_text(candidate.fields.get("author", ""))
+    if not candidate_author:
+        return False
+    candidate_tokens = set(re.findall(r"[a-z0-9]+", candidate_author))
+    return bool(author_tokens & candidate_tokens)
+
+
+def _datacite_work_to_entry(data: dict) -> BibEntry:
+    attributes = data.get("attributes", {})
+    doi = str(attributes.get("doi") or "")
+    titles = attributes.get("titles") or []
+    creators = attributes.get("creators") or []
+    descriptions = attributes.get("descriptions") or []
+    publisher = str(attributes.get("publisher") or "")
+    year = str(attributes.get("publicationYear") or "")
+    url = str(attributes.get("url") or "")
+    types = attributes.get("types") or {}
+
+    title = titles[0].get("title", "") if titles else ""
+    author_names = " and ".join(_datacite_creator_name(creator) for creator in creators if _datacite_creator_name(creator))
+    abstract = _datacite_abstract(descriptions)
+    entry_type = _datacite_type_to_bibtype(str(types.get("resourceTypeGeneral") or ""))
+
+    fields: dict[str, str] = {}
+    if title:
+        fields["title"] = title
+    if author_names:
+        fields["author"] = author_names
+    if year:
+        fields["year"] = year
+    if doi:
+        fields["doi"] = doi
+    if url:
+        fields["url"] = url
+    elif doi:
+        fields["url"] = f"https://doi.org/{doi}"
+    if publisher:
+        fields["publisher"] = publisher
+    if abstract:
+        fields["abstract"] = abstract
+
+    citation_key = _make_resolution_key(author_names or "datacite", year or "n.d.", title or doi or "untitled")
+    return BibEntry(entry_type=entry_type, citation_key=citation_key, fields=fields)
+
+
+def _datacite_creator_name(creator: dict) -> str:
+    family = str(creator.get("familyName") or "")
+    given = str(creator.get("givenName") or "")
+    if family and given:
+        return f"{family}, {given}"
+    return str(creator.get("name") or family or given)
+
+
+def _datacite_abstract(descriptions: list[dict]) -> str:
+    for description in descriptions:
+        if str(description.get("descriptionType") or "").lower() == "abstract":
+            return str(description.get("description") or "")
+    return ""
+
+
+def _datacite_type_to_bibtype(resource_type: str) -> str:
+    lowered = resource_type.lower()
+    mapping = {
+        "audiovisual": "misc",
+        "book": "book",
+        "bookchapter": "incollection",
+        "collection": "misc",
+        "computationalnotebook": "misc",
+        "conferencepaper": "inproceedings",
+        "dataset": "misc",
+        "dissertation": "phdthesis",
+        "image": "misc",
+        "journalarticle": "article",
+        "model": "misc",
+        "report": "techreport",
+        "software": "misc",
+        "text": "misc",
+    }
+    return mapping.get(lowered, "misc")

src/citegeist/sources.py

@@ -30,11 +30,11 @@ class SourceClient:
     def get_text(self, url: str) -> str:
         cached = self._read_cached(url, "txt")
         if cached is not None:
-            return cached.decode("utf-8")
+            return self._decode_text(cached)
 
         payload = self._fetch_bytes(url)
         self._write_cache(url, "txt", payload)
-        return payload.decode("utf-8")
+        return self._decode_text(payload)
 
     def get_xml(self, url: str) -> ET.Element:
         cached = self._read_cached(url, "xml")
@@ -76,3 +76,11 @@ class SourceClient:
         self.cache_dir.mkdir(parents=True, exist_ok=True)
         path = self.cache_dir / self._cache_key(url, suffix)
         path.write_bytes(payload)
+
+    def _decode_text(self, payload: bytes) -> str:
+        for encoding in ("utf-8", "utf-8-sig", "iso-8859-1", "latin-1"):
+            try:
+                return payload.decode(encoding)
+            except UnicodeDecodeError:
+                continue
+        return payload.decode("utf-8", errors="replace")

src/citegeist/storage.py

@@ -95,6 +95,29 @@ class BibliographyStore:
                 PRIMARY KEY (source_entry_id, target_citation_key, relation_type)
             );
 
+            CREATE TABLE IF NOT EXISTS topics (
+                id INTEGER PRIMARY KEY,
+                slug TEXT NOT NULL UNIQUE,
+                name TEXT NOT NULL,
+                source_type TEXT NOT NULL,
+                source_url TEXT,
+                expansion_phrase TEXT,
+                suggested_phrase TEXT,
+                phrase_review_status TEXT NOT NULL DEFAULT 'unreviewed',
+                phrase_review_notes TEXT,
+                created_at TEXT NOT NULL DEFAULT CURRENT_TIMESTAMP,
+                updated_at TEXT NOT NULL DEFAULT CURRENT_TIMESTAMP
+            );
+
+            CREATE TABLE IF NOT EXISTS entry_topics (
+                entry_id INTEGER NOT NULL REFERENCES entries(id) ON DELETE CASCADE,
+                topic_id INTEGER NOT NULL REFERENCES topics(id) ON DELETE CASCADE,
+                source_label TEXT NOT NULL,
+                confidence REAL,
+                created_at TEXT NOT NULL DEFAULT CURRENT_TIMESTAMP,
+                PRIMARY KEY (entry_id, topic_id)
+            );
+
             CREATE TABLE IF NOT EXISTS field_provenance (
                 id INTEGER PRIMARY KEY,
                 entry_id INTEGER NOT NULL REFERENCES entries(id) ON DELETE CASCADE,
@@ -117,10 +140,23 @@ class BibliographyStore:
                 confidence REAL,
                 recorded_at TEXT NOT NULL DEFAULT CURRENT_TIMESTAMP
             );
+
+            CREATE TABLE IF NOT EXISTS field_conflicts (
+                id INTEGER PRIMARY KEY,
+                entry_id INTEGER NOT NULL REFERENCES entries(id) ON DELETE CASCADE,
+                field_name TEXT NOT NULL,
+                current_value TEXT,
+                proposed_value TEXT,
+                source_type TEXT NOT NULL,
+                source_label TEXT NOT NULL,
+                status TEXT NOT NULL DEFAULT 'open',
+                recorded_at TEXT NOT NULL DEFAULT CURRENT_TIMESTAMP
+            );
             """
         )
 
         self._ensure_entry_columns()
+        self._ensure_topic_columns()
 
         if self._fts5_enabled:
             self.connection.execute(
@@ -177,6 +213,7 @@ class BibliographyStore:
             ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
             ON CONFLICT(citation_key) DO UPDATE SET
                 entry_type = excluded.entry_type,
+                review_status = excluded.review_status,
                 title = excluded.title,
                 year = excluded.year,
                 journal = excluded.journal,
@@ -280,30 +317,58 @@ class BibliographyStore:
 
         return entry_id
 
-    def search_text(self, query: str, limit: int = 10) -> list[dict[str, object]]:
+    def search_text(self, query: str, limit: int = 10, topic_slug: str | None = None) -> list[dict[str, object]]:
         if self._fts5_enabled:
-            rows = self.connection.execute(
+            if topic_slug:
-                """
+                rows = self.connection.execute(
-                SELECT e.citation_key, e.title, e.year, bm25(entry_text_fts) AS score
+                    """
-                FROM entry_text_fts
+                    SELECT DISTINCT e.citation_key, e.title, e.year, bm25(entry_text_fts) AS score
-                JOIN entries e ON e.citation_key = entry_text_fts.citation_key
+                    FROM entry_text_fts
-                WHERE entry_text_fts MATCH ?
+                    JOIN entries e ON e.citation_key = entry_text_fts.citation_key
-                ORDER BY score
+                    JOIN entry_topics et ON et.entry_id = e.id
-                LIMIT ?
+                    JOIN topics t ON t.id = et.topic_id
-                """,
+                    WHERE entry_text_fts MATCH ? AND t.slug = ?
-                (query, limit),
+                    ORDER BY score
-            ).fetchall()
+                    LIMIT ?
+                    """,
+                    (query, topic_slug, limit),
+                ).fetchall()
+            else:
+                rows = self.connection.execute(
+                    """
+                    SELECT e.citation_key, e.title, e.year, bm25(entry_text_fts) AS score
+                    FROM entry_text_fts
+                    JOIN entries e ON e.citation_key = entry_text_fts.citation_key
+                    WHERE entry_text_fts MATCH ?
+                    ORDER BY score
+                    LIMIT ?
+                    """,
+                    (query, limit),
+                ).fetchall()
         else:
             pattern = f"%{query}%"
-            rows = self.connection.execute(
+            if topic_slug:
-                """
+                rows = self.connection.execute(
-                SELECT citation_key, title, year, 0.0 AS score
+                    """
-                FROM entries
+                    SELECT DISTINCT e.citation_key, e.title, e.year, 0.0 AS score
-                WHERE title LIKE ? OR abstract LIKE ? OR fulltext LIKE ?
+                    FROM entries e
-                LIMIT ?
+                    JOIN entry_topics et ON et.entry_id = e.id
-                """,
+                    JOIN topics t ON t.id = et.topic_id
-                (pattern, pattern, pattern, limit),
+                    WHERE t.slug = ? AND (e.title LIKE ? OR e.abstract LIKE ? OR e.fulltext LIKE ?)
-            ).fetchall()
+                    LIMIT ?
+                    """,
+                    (topic_slug, pattern, pattern, pattern, limit),
+                ).fetchall()
+            else:
+                rows = self.connection.execute(
+                    """
+                    SELECT citation_key, title, year, 0.0 AS score
+                    FROM entries
+                    WHERE title LIKE ? OR abstract LIKE ? OR fulltext LIKE ?
+                    LIMIT ?
+                    """,
+                    (pattern, pattern, pattern, limit),
+                ).fetchall()
 
         return [dict(row) for row in rows]
 
@@ -383,7 +448,11 @@ class BibliographyStore:
             "SELECT * FROM entries WHERE citation_key = ?",
             (citation_key,),
         ).fetchone()
-        return self._row_to_entry_dict(row) if row else None
+        if row is None:
+            return None
+        payload = self._row_to_entry_dict(row)
+        payload["topics"] = self.get_entry_topics(citation_key)
+        return payload
 
     def list_entries(self, limit: int = 50) -> list[dict[str, object]]:
         rows = self.connection.execute(
@@ -397,6 +466,227 @@ class BibliographyStore:
         ).fetchall()
         return [dict(row) for row in rows]
 
+    def ensure_topic(
+        self,
+        slug: str,
+        name: str,
+        source_type: str = "manual",
+        source_url: str | None = None,
+        expansion_phrase: str | None = None,
+        suggested_phrase: str | None = None,
+        phrase_review_status: str | None = None,
+        phrase_review_notes: str | None = None,
+    ) -> int:
+        row = self.connection.execute(
+            """
+            INSERT INTO topics (
+                slug, name, source_type, source_url, expansion_phrase,
+                suggested_phrase, phrase_review_status, phrase_review_notes
+            )
+            VALUES (?, ?, ?, ?, ?, ?, COALESCE(?, 'unreviewed'), ?)
+            ON CONFLICT(slug) DO UPDATE SET
+                name = excluded.name,
+                source_type = excluded.source_type,
+                source_url = COALESCE(excluded.source_url, topics.source_url),
+                expansion_phrase = COALESCE(excluded.expansion_phrase, topics.expansion_phrase),
+                suggested_phrase = COALESCE(excluded.suggested_phrase, topics.suggested_phrase),
+                phrase_review_status = COALESCE(excluded.phrase_review_status, topics.phrase_review_status),
+                phrase_review_notes = COALESCE(excluded.phrase_review_notes, topics.phrase_review_notes),
+                updated_at = CURRENT_TIMESTAMP
+            RETURNING id
+            """,
+            (
+                slug,
+                name,
+                source_type,
+                source_url,
+                expansion_phrase,
+                suggested_phrase,
+                phrase_review_status,
+                phrase_review_notes,
+            ),
+        ).fetchone()
+        return int(row["id"])
+
+    def add_entry_topic(
+        self,
+        citation_key: str,
+        topic_slug: str,
+        topic_name: str,
+        source_type: str = "manual",
+        source_url: str | None = None,
+        source_label: str = "manual",
+        confidence: float = 1.0,
+        expansion_phrase: str | None = None,
+    ) -> bool:
+        entry_row = self.connection.execute(
+            "SELECT id FROM entries WHERE citation_key = ?",
+            (citation_key,),
+        ).fetchone()
+        if entry_row is None:
+            return False
+
+        topic_id = self.ensure_topic(
+            topic_slug,
+            topic_name,
+            source_type=source_type,
+            source_url=source_url,
+            expansion_phrase=expansion_phrase,
+        )
+        self.connection.execute(
+            """
+            INSERT INTO entry_topics (entry_id, topic_id, source_label, confidence)
+            VALUES (?, ?, ?, ?)
+            ON CONFLICT(entry_id, topic_id) DO UPDATE SET
+                source_label = excluded.source_label,
+                confidence = excluded.confidence
+            """,
+            (int(entry_row["id"]), topic_id, source_label, confidence),
+        )
+        return True
+
+    def get_entry_topics(self, citation_key: str) -> list[dict[str, object]]:
+        rows = self.connection.execute(
+            """
+            SELECT t.slug, t.name, t.source_type, t.source_url, et.source_label, et.confidence
+            FROM entry_topics et
+            JOIN entries e ON e.id = et.entry_id
+            JOIN topics t ON t.id = et.topic_id
+            WHERE e.citation_key = ?
+            ORDER BY t.name, t.slug
+            """,
+            (citation_key,),
+        ).fetchall()
+        return [dict(row) for row in rows]
+
+    def list_topics(
+        self,
+        limit: int = 100,
+        phrase_review_status: str | None = None,
+    ) -> list[dict[str, object]]:
+        where = ""
+        params: list[object] = []
+        if phrase_review_status is not None:
+            where = "WHERE t.phrase_review_status = ?"
+            params.append(phrase_review_status)
+        params.append(limit)
+        rows = self.connection.execute(
+            f"""
+            SELECT t.slug, t.name, t.source_type, t.source_url, t.expansion_phrase,
+                   t.suggested_phrase, t.phrase_review_status, t.phrase_review_notes,
+                   COUNT(et.entry_id) AS entry_count
+            FROM topics t
+            LEFT JOIN entry_topics et ON et.topic_id = t.id
+            {where}
+            GROUP BY t.id, t.slug, t.name, t.source_type, t.source_url, t.expansion_phrase,
+                     t.suggested_phrase, t.phrase_review_status, t.phrase_review_notes
+            ORDER BY t.name, t.slug
+            LIMIT ?
+            """,
+            params,
+        ).fetchall()
+        return [dict(row) for row in rows]
+
+    def get_topic(self, slug: str) -> dict[str, object] | None:
+        row = self.connection.execute(
+            """
+            SELECT t.slug, t.name, t.source_type, t.source_url, t.expansion_phrase,
+                   t.suggested_phrase, t.phrase_review_status, t.phrase_review_notes,
+                   COUNT(et.entry_id) AS entry_count
+            FROM topics t
+            LEFT JOIN entry_topics et ON et.topic_id = t.id
+            WHERE t.slug = ?
+            GROUP BY t.id, t.slug, t.name, t.source_type, t.source_url, t.expansion_phrase,
+                     t.suggested_phrase, t.phrase_review_status, t.phrase_review_notes
+            """,
+            (slug,),
+        ).fetchone()
+        return dict(row) if row else None
+
+    def set_topic_expansion_phrase(self, slug: str, expansion_phrase: str | None) -> bool:
+        row = self.connection.execute(
+            """
+            UPDATE topics
+            SET expansion_phrase = ?, updated_at = CURRENT_TIMESTAMP
+            WHERE slug = ?
+            RETURNING id
+            """,
+            (expansion_phrase, slug),
+        ).fetchone()
+        self.connection.commit()
+        return row is not None
+
+    def stage_topic_phrase_suggestion(
+        self,
+        slug: str,
+        suggested_phrase: str | None,
+        review_status: str = "pending",
+        review_notes: str | None = None,
+    ) -> bool:
+        row = self.connection.execute(
+            """
+            UPDATE topics
+            SET suggested_phrase = ?,
+                phrase_review_status = ?,
+                phrase_review_notes = ?,
+                updated_at = CURRENT_TIMESTAMP
+            WHERE slug = ?
+            RETURNING id
+            """,
+            (suggested_phrase, review_status, review_notes, slug),
+        ).fetchone()
+        self.connection.commit()
+        return row is not None
+
+    def review_topic_phrase_suggestion(
+        self,
+        slug: str,
+        review_status: str,
+        review_notes: str | None = None,
+        applied_phrase: str | None = None,
+    ) -> bool:
+        topic = self.get_topic(slug)
+        if topic is None:
+            return False
+
+        suggested_phrase = topic.get("suggested_phrase")
+        expansion_phrase = topic.get("expansion_phrase")
+        if review_status == "accepted":
+            expansion_phrase = applied_phrase if applied_phrase is not None else suggested_phrase
+        elif applied_phrase is not None:
+            expansion_phrase = applied_phrase
+
+        row = self.connection.execute(
+            """
+            UPDATE topics
+            SET expansion_phrase = ?,
+                phrase_review_status = ?,
+                phrase_review_notes = ?,
+                updated_at = CURRENT_TIMESTAMP
+            WHERE slug = ?
+            RETURNING id
+            """,
+            (expansion_phrase, review_status, review_notes, slug),
+        ).fetchone()
+        self.connection.commit()
+        return row is not None
+
+    def list_topic_entries(self, topic_slug: str, limit: int = 100) -> list[dict[str, object]]:
+        rows = self.connection.execute(
+            """
+            SELECT e.citation_key, e.entry_type, e.review_status, e.title, e.year,
+                   t.slug AS topic_slug, t.name AS topic_name, et.source_label, et.confidence
+            FROM entry_topics et
+            JOIN topics t ON t.id = et.topic_id
+            JOIN entries e ON e.id = et.entry_id
+            WHERE t.slug = ?
+            ORDER BY COALESCE(e.year, ''), e.citation_key
+            LIMIT ?
+            """,
+            (topic_slug, limit),
+        ).fetchall()
+        return [dict(row) for row in rows]
+
     def set_entry_status(self, citation_key: str, review_status: str) -> bool:
         row = self.connection.execute(
             """
@@ -437,6 +727,114 @@ class BibliographyStore:
         self.connection.commit()
         return True
 
+    def record_conflicts(
+        self,
+        citation_key: str,
+        conflicts: list[dict[str, str]],
+        source_type: str,
+        source_label: str,
+    ) -> bool:
+        row = self.connection.execute(
+            "SELECT id FROM entries WHERE citation_key = ?",
+            (citation_key,),
+        ).fetchone()
+        if row is None:
+            return False
+
+        entry_id = int(row["id"])
+        for conflict in conflicts:
+            self.connection.execute(
+                """
+                INSERT INTO field_conflicts (
+                    entry_id, field_name, current_value, proposed_value, source_type, source_label, status
+                ) VALUES (?, ?, ?, ?, ?, ?, 'open')
+                """,
+                (
+                    entry_id,
+                    conflict["field_name"],
+                    conflict.get("current_value"),
+                    conflict.get("proposed_value"),
+                    source_type,
+                    source_label,
+                ),
+            )
+        self.connection.commit()
+        return True
+
+    def get_field_conflicts(self, citation_key: str, status: str | None = None) -> list[dict[str, object]]:
+        where = ""
+        params: list[object] = [citation_key]
+        if status is not None:
+            where = " AND fc.status = ?"
+            params.append(status)
+
+        rows = self.connection.execute(
+            f"""
+            SELECT fc.field_name, fc.current_value, fc.proposed_value, fc.source_type,
+                   fc.source_label, fc.status, fc.recorded_at
+            FROM field_conflicts fc
+            JOIN entries e ON e.id = fc.entry_id
+            WHERE e.citation_key = ?{where}
+            ORDER BY fc.recorded_at, fc.id
+            """,
+            params,
+        ).fetchall()
+        return [dict(row) for row in rows]
+
+    def set_conflict_status(self, citation_key: str, field_name: str, status: str) -> int:
+        row = self.connection.execute(
+            "SELECT id FROM entries WHERE citation_key = ?",
+            (citation_key,),
+        ).fetchone()
+        if row is None:
+            return 0
+        entry_id = int(row["id"])
+        result = self.connection.execute(
+            """
+            UPDATE field_conflicts
+            SET status = ?
+            WHERE entry_id = ? AND field_name = ? AND status = 'open'
+            """,
+            (status, entry_id, field_name),
+        )
+        self.connection.commit()
+        return result.rowcount
+
+    def apply_conflict_value(self, citation_key: str, field_name: str) -> bool:
+        row = self.connection.execute(
+            """
+            SELECT fc.id, fc.proposed_value, e.review_status
+            FROM field_conflicts fc
+            JOIN entries e ON e.id = fc.entry_id
+            WHERE e.citation_key = ? AND fc.field_name = ? AND fc.status = 'open'
+            ORDER BY fc.recorded_at DESC, fc.id DESC
+            LIMIT 1
+            """,
+            (citation_key, field_name),
+        ).fetchone()
+        if row is None:
+            return False
+
+        entry = self._load_bib_entry(citation_key)
+        if entry is None:
+            return False
+
+        proposed_value = str(row["proposed_value"] or "")
+        entry.fields[field_name] = proposed_value
+        self.upsert_entry(
+            entry,
+            raw_bibtex=_entry_to_bibtex(entry),
+            source_type="manual_review",
+            source_label=f"conflict_accept:{field_name}",
+            review_status=str(row["review_status"] or "draft"),
+        )
+        self.connection.execute(
+            "UPDATE field_conflicts SET status = 'accepted' WHERE id = ?",
+            (int(row["id"]),),
+        )
+        self.connection.commit()
+        return True
+
     def add_relation(
         self,
         source_citation_key: str,
@@ -651,6 +1049,37 @@ class BibliographyStore:
                 "ALTER TABLE entries ADD COLUMN review_status TEXT NOT NULL DEFAULT 'draft'"
             )
 
+    def _ensure_topic_columns(self) -> None:
+        columns = {
+            row["name"] for row in self.connection.execute("PRAGMA table_info(topics)").fetchall()
+        }
+        if "expansion_phrase" not in columns:
+            try:
+                self.connection.execute("ALTER TABLE topics ADD COLUMN expansion_phrase TEXT")
+            except sqlite3.OperationalError as exc:
+                if "duplicate column name" not in str(exc).lower():
+                    raise
+        if "suggested_phrase" not in columns:
+            try:
+                self.connection.execute("ALTER TABLE topics ADD COLUMN suggested_phrase TEXT")
+            except sqlite3.OperationalError as exc:
+                if "duplicate column name" not in str(exc).lower():
+                    raise
+        if "phrase_review_status" not in columns:
+            try:
+                self.connection.execute(
+                    "ALTER TABLE topics ADD COLUMN phrase_review_status TEXT NOT NULL DEFAULT 'unreviewed'"
+                )
+            except sqlite3.OperationalError as exc:
+                if "duplicate column name" not in str(exc).lower():
+                    raise
+        if "phrase_review_notes" not in columns:
+            try:
+                self.connection.execute("ALTER TABLE topics ADD COLUMN phrase_review_notes TEXT")
+            except sqlite3.OperationalError as exc:
+                if "duplicate column name" not in str(exc).lower():
+                    raise
+
     def _record_field_provenance(
         self,
         entry_id: int,

tests/test_batch.py

@@ -0,0 +1,129 @@
+from pathlib import Path
+
+from citegeist.batch import BatchBootstrapRunner, load_batch_jobs
+from citegeist.cli import main
+from citegeist.storage import BibliographyStore
+
+
+def test_load_batch_jobs_accepts_object_with_jobs(tmp_path: Path):
+    path = tmp_path / "jobs.json"
+    path.write_text(
+        """
+{
+  "jobs": [
+    {"name": "topic-only", "topic": "graph topic"},
+    {"name": "seed-only", "seed_bib": "seed.bib"}
+  ]
+}
+""",
+        encoding="utf-8",
+    )
+
+    jobs = load_batch_jobs(path)
+
+    assert jobs[0]["name"] == "topic-only"
+    assert jobs[1]["seed_bib"] == str((tmp_path / "seed.bib").resolve())
+
+
+def test_batch_runner_executes_multiple_jobs(tmp_path: Path):
+    seed_bib = tmp_path / "seed.bib"
+    seed_bib.write_text(
+        """
+@article{seed2024,
+  author = {Seed, Alice},
+  title = {Seed Paper},
+  year = {2024}
+}
+""",
+        encoding="utf-8",
+    )
+    jobs = [
+        {"name": "seed-job", "seed_bib": str(seed_bib), "expand": False},
+        {"name": "topic-job", "topic": "graph topic", "expand": False, "preview": True},
+    ]
+
+    runner = BatchBootstrapRunner()
+    from citegeist import BibEntry
+
+    runner.bootstrapper.resolver.search_openalex = lambda topic, limit=5: [  # type: ignore[method-assign]
+        BibEntry(entry_type="article", citation_key="topic2024graph", fields={"title": "Graph Topic Result"})
+    ]
+    runner.bootstrapper.resolver.search_crossref = lambda topic, limit=5: []  # type: ignore[method-assign]
+    runner.bootstrapper.resolver.search_datacite = lambda topic, limit=5: []  # type: ignore[method-assign]
+
+    store = BibliographyStore()
+    try:
+        results = runner.run(store, jobs)
+        assert [job.job_name for job in results] == ["seed-job", "topic-job"]
+        assert results[0].result_count == 1
+        assert results[1].results[0].citation_key == "topic2024graph"
+        assert store.get_entry("seed2024") is not None
+        assert store.get_entry("topic2024graph") is None
+    finally:
+        store.close()
+
+
+def test_batch_runner_can_store_topic_phrase_metadata():
+    jobs = [
+        {
+            "name": "topic-job",
+            "topic": "graph topic",
+            "topic_slug": "graph-methods",
+            "topic_name": "Graph Methods",
+            "topic_phrase": "graph networks biology",
+            "expand": False,
+            "preview": False,
+        }
+    ]
+
+    runner = BatchBootstrapRunner()
+    from citegeist import BibEntry
+
+    runner.bootstrapper.resolver.search_openalex = lambda topic, limit=5: [  # type: ignore[method-assign]
+        BibEntry(entry_type="article", citation_key="topic2024graph", fields={"title": "Graph Topic Result"})
+    ]
+    runner.bootstrapper.resolver.search_crossref = lambda topic, limit=5: []  # type: ignore[method-assign]
+    runner.bootstrapper.resolver.search_datacite = lambda topic, limit=5: []  # type: ignore[method-assign]
+
+    store = BibliographyStore()
+    try:
+        runner.run(store, jobs)
+        topic = store.get_topic("graph-methods")
+        assert topic is not None
+        assert topic["name"] == "Graph Methods"
+        assert topic["expansion_phrase"] == "graph networks biology"
+    finally:
+        store.close()
+
+
+def test_bootstrap_batch_cli_runs_json_jobs(tmp_path: Path):
+    seed_bib = tmp_path / "seed.bib"
+    seed_bib.write_text(
+        """
+@article{seed2024,
+  author = {Seed, Alice},
+  title = {Seed Paper},
+  year = {2024}
+}
+""",
+        encoding="utf-8",
+    )
+    batch_json = tmp_path / "jobs.json"
+    batch_json.write_text(
+        f"""
+[
+  {{"name": "seed-job", "seed_bib": "{seed_bib}", "expand": false}},
+  {{"name": "topic-job", "topic": "graph topic", "expand": false, "preview": true}}
+]
+""",
+        encoding="utf-8",
+    )
+
+    from unittest.mock import patch
+
+    database = tmp_path / "library.sqlite3"
+    with patch("citegeist.cli.BatchBootstrapRunner.run") as mocked_run:
+        mocked_run.return_value = []
+        exit_code = main(["--db", str(database), "bootstrap-batch", str(batch_json)])
+
+    assert exit_code == 0

tests/test_bootstrap.py

@@ -0,0 +1,175 @@
+from citegeist import BibliographyStore
+from citegeist.bootstrap import Bootstrapper
+from citegeist.cli import main
+
+
+def test_bootstrap_from_seed_bib_only():
+    store = BibliographyStore()
+    try:
+        bootstrapper = Bootstrapper()
+        bootstrapper.crossref_expander.expand_entry_references = lambda _store, _key: []  # type: ignore[method-assign]
+        bootstrapper.openalex_expander.expand_entry = lambda _store, _key, relation_type="cites", limit=5: []  # type: ignore[method-assign]
+
+        results = bootstrapper.bootstrap(
+            store,
+            seed_bibtex="""
+@article{seed2024,
+  author = {Seed, Alice},
+  title = {Seed Paper},
+  year = {2024}
+}
+""",
+            expand=False,
+        )
+
+        assert [item.citation_key for item in results] == ["seed2024"]
+        assert store.get_entry("seed2024") is not None
+    finally:
+        store.close()
+
+
+def test_bootstrap_from_topic_only():
+    store = BibliographyStore()
+    try:
+        bootstrapper = Bootstrapper()
+        bootstrapper.resolver.search_openalex = lambda topic, limit=5: []  # type: ignore[method-assign]
+        bootstrapper.resolver.search_crossref = lambda topic, limit=5: []  # type: ignore[method-assign]
+        bootstrapper.resolver.search_datacite = lambda topic, limit=5: [  # type: ignore[method-assign]
+            __import__("citegeist").BibEntry(
+                entry_type="article",
+                citation_key="topic2024graph",
+                fields={"title": "Graph Topic Result", "year": "2024"},
+            )
+        ]
+        bootstrapper.crossref_expander.expand_entry_references = lambda _store, _key: []  # type: ignore[method-assign]
+        bootstrapper.openalex_expander.expand_entry = lambda _store, _key, relation_type="cites", limit=5: []  # type: ignore[method-assign]
+
+        results = bootstrapper.bootstrap(store, topic="graph topic", expand=False)
+
+        assert [item.citation_key for item in results] == ["topic2024graph"]
+        assert store.get_entry("topic2024graph") is not None
+        assert results[0].score > 0
+    finally:
+        store.close()
+
+
+def test_bootstrap_cli_accepts_seed_and_topic(tmp_path):
+    seed_bib = tmp_path / "seed.bib"
+    seed_bib.write_text(
+        """
+@article{seed2024,
+  author = {Seed, Alice},
+  title = {Seed Paper},
+  year = {2024}
+}
+""",
+        encoding="utf-8",
+    )
+
+    from unittest.mock import patch
+
+    database = tmp_path / "library.sqlite3"
+    with patch("citegeist.cli.Bootstrapper.bootstrap") as mocked_bootstrap:
+        mocked_bootstrap.return_value = []
+        exit_code = main(
+            [
+                "--db",
+                str(database),
+                "bootstrap",
+                "--seed-bib",
+                str(seed_bib),
+                "--topic",
+                "graph topic",
+                "--no-expand",
+            ]
+        )
+
+    assert exit_code == 0
+
+
+def test_bootstrap_ranks_and_deduplicates_topic_candidates():
+    store = BibliographyStore()
+    try:
+        bootstrapper = Bootstrapper()
+        from citegeist import BibEntry
+
+        bootstrapper.resolver.search_openalex = lambda topic, limit=5: [  # type: ignore[method-assign]
+            BibEntry(
+                entry_type="article",
+                citation_key="shared2024graph",
+                fields={"title": "Graph Topic Ranking", "abstract": "graph topic graph"},
+            )
+        ]
+        bootstrapper.resolver.search_crossref = lambda topic, limit=5: [  # type: ignore[method-assign]
+            BibEntry(
+                entry_type="article",
+                citation_key="shared2024graph",
+                fields={"title": "Graph Topic Ranking", "abstract": "graph"},
+            ),
+            BibEntry(
+                entry_type="article",
+                citation_key="crossref2024other",
+                fields={"title": "Less relevant paper"},
+            ),
+        ]
+        bootstrapper.resolver.search_datacite = lambda topic, limit=5: []  # type: ignore[method-assign]
+        bootstrapper.crossref_expander.expand_entry_references = lambda _store, _key: []  # type: ignore[method-assign]
+        bootstrapper.openalex_expander.expand_entry = lambda _store, _key, relation_type="cites", limit=5: []  # type: ignore[method-assign]
+
+        results = bootstrapper.bootstrap(store, topic="graph topic", expand=False, topic_limit=5)
+
+        topic_results = [item for item in results if item.origin == "topic"]
+        assert [item.citation_key for item in topic_results] == ["shared2024graph", "crossref2024other"]
+        assert topic_results[0].score > topic_results[1].score
+    finally:
+        store.close()
+
+
+def test_bootstrap_preview_does_not_write_to_database():
+    store = BibliographyStore()
+    try:
+        bootstrapper = Bootstrapper()
+        from citegeist import BibEntry
+
+        bootstrapper.resolver.search_openalex = lambda topic, limit=5: [  # type: ignore[method-assign]
+            BibEntry(entry_type="article", citation_key="preview2024graph", fields={"title": "Preview Graph Topic"})
+        ]
+        bootstrapper.resolver.search_crossref = lambda topic, limit=5: []  # type: ignore[method-assign]
+        bootstrapper.resolver.search_datacite = lambda topic, limit=5: []  # type: ignore[method-assign]
+
+        results = bootstrapper.bootstrap(store, topic="graph topic", expand=False, preview_only=True)
+
+        assert [item.citation_key for item in results] == ["preview2024graph"]
+        assert store.get_entry("preview2024graph") is None
+    finally:
+        store.close()
+
+
+def test_bootstrap_topic_commit_limit_restricts_persisted_candidates():
+    store = BibliographyStore()
+    try:
+        bootstrapper = Bootstrapper()
+        from citegeist import BibEntry
+
+        bootstrapper.resolver.search_openalex = lambda topic, limit=5: [  # type: ignore[method-assign]
+            BibEntry(entry_type="article", citation_key="rank1", fields={"title": "Graph Topic One"}),
+            BibEntry(entry_type="article", citation_key="rank2", fields={"title": "Graph Topic Two"}),
+        ]
+        bootstrapper.resolver.search_crossref = lambda topic, limit=5: []  # type: ignore[method-assign]
+        bootstrapper.resolver.search_datacite = lambda topic, limit=5: []  # type: ignore[method-assign]
+        bootstrapper.crossref_expander.expand_entry_references = lambda _store, _key: []  # type: ignore[method-assign]
+        bootstrapper.openalex_expander.expand_entry = lambda _store, _key, relation_type="cites", limit=5: []  # type: ignore[method-assign]
+
+        results = bootstrapper.bootstrap(
+            store,
+            topic="graph topic",
+            expand=False,
+            topic_limit=5,
+            topic_commit_limit=1,
+        )
+
+        assert [item.citation_key for item in results if item.origin == "topic"] == ["rank1"]
+        assert store.get_entry("rank1") is not None
+        assert store.get_entry("rank2") is None
+    finally:
+        store.close()

tests/test_cli.py

@@ -119,7 +119,7 @@ def test_cli_resolve_updates_entry(tmp_path: Path):
                 citation_key="resolvedkey",
                 fields={
                     "author": "Smith, Jane",
-                    "title": "Graph-first bibliography augmentation",
+                    "title": "Resolved Graph-first bibliography augmentation",
                     "year": "2024",
                     "doi": "10.1000/example-doi",
                     "journal": "Journal of Graph Studies",
@@ -138,6 +138,803 @@ def test_cli_resolve_updates_entry(tmp_path: Path):
         )
 
     assert exit_code == 0
+    show = run_cli(tmp_path, "show", "--conflicts", "smith2024graphs")
+    assert show.returncode == 0
+    payload = json.loads(show.stdout)
+    assert payload["field_conflicts"][0]["field_name"] == "title"
+
+
+def test_cli_resolve_conflicts_updates_status(tmp_path: Path):
+    bib_path = tmp_path / "input.bib"
+    bib_path.write_text(
+        """
+@article{smith2024graphs,
+  author = {Smith, Jane},
+  title = {Graph-first bibliography augmentation},
+  year = {2024}
+}
+""",
+        encoding="utf-8",
+    )
+    ingest = run_cli(tmp_path, "ingest", str(bib_path))
+    assert ingest.returncode == 0
+
+    from citegeist.storage import BibliographyStore
+
+    database = tmp_path / "library.sqlite3"
+    store = BibliographyStore(database)
+    try:
+        store.record_conflicts(
+            "smith2024graphs",
+            [
+                {
+                    "field_name": "title",
+                    "current_value": "Graph-first bibliography augmentation",
+                    "proposed_value": "Resolved title",
+                }
+            ],
+            source_type="resolver",
+            source_label="openalex:search:Graph-first bibliography augmentation",
+        )
+    finally:
+        store.close()
+
+    result = run_cli(tmp_path, "resolve-conflicts", "smith2024graphs", "title", "accepted")
+    assert result.returncode == 0
+    assert "accepted" in result.stdout
+
+
+def test_cli_apply_conflict_updates_entry_value(tmp_path: Path):
+    bib_path = tmp_path / "input.bib"
+    bib_path.write_text(
+        """
+@article{smith2024graphs,
+  author = {Smith, Jane},
+  title = {Graph-first bibliography augmentation},
+  year = {2024}
+}
+""",
+        encoding="utf-8",
+    )
+    ingest = run_cli(tmp_path, "ingest", str(bib_path))
+    assert ingest.returncode == 0
+
+    from citegeist.storage import BibliographyStore
+
+    database = tmp_path / "library.sqlite3"
+    store = BibliographyStore(database)
+    try:
+        store.record_conflicts(
+            "smith2024graphs",
+            [
+                {
+                    "field_name": "title",
+                    "current_value": "Graph-first bibliography augmentation",
+                    "proposed_value": "Resolved Graph-first bibliography augmentation",
+                }
+            ],
+            source_type="resolver",
+            source_label="openalex:search:Graph-first bibliography augmentation",
+        )
+    finally:
+        store.close()
+
+    result = run_cli(tmp_path, "apply-conflict", "smith2024graphs", "title")
+    assert result.returncode == 0
+    assert "applied" in result.stdout
+
+    show = run_cli(tmp_path, "show", "smith2024graphs")
+    payload = json.loads(show.stdout)
+    assert payload["title"] == "Resolved Graph-first bibliography augmentation"
+
+
+def test_cli_discover_oai_outputs_identity_and_sets():
+    from unittest.mock import patch
+    from citegeist.harvest import OaiMetadataFormat, OaiSet
+
+    with patch("citegeist.cli.OaiPmhHarvester.identify") as mocked_identify, patch(
+        "citegeist.cli.OaiPmhHarvester.list_sets"
+    ) as mocked_sets, patch("citegeist.cli.OaiPmhHarvester.list_metadata_formats") as mocked_formats:
+        mocked_identify.return_value = {
+            "repositoryName": "Example Repository",
+            "granularity": "YYYY-MM-DD",
+        }
+        mocked_formats.return_value = [
+            OaiMetadataFormat(
+                metadata_prefix="oai_dc",
+                schema="http://www.openarchives.org/OAI/2.0/oai_dc.xsd",
+                metadata_namespace="http://www.openarchives.org/OAI/2.0/oai_dc/",
+            )
+        ]
+        mocked_sets.return_value = [
+            OaiSet(set_spec="theses", set_name="Theses", set_description="Graduate theses")
+        ]
+        exit_code = main(["discover-oai", "https://example.edu/oai"])
+
+    assert exit_code == 0
+
+
+def test_cli_bootstrap_preview_mode(tmp_path):
+    from unittest.mock import patch
+
+    database = tmp_path / "library.sqlite3"
+    with patch("citegeist.cli.Bootstrapper.bootstrap") as mocked_bootstrap:
+        mocked_bootstrap.return_value = []
+        exit_code = main(
+            [
+                "--db",
+                str(database),
+                "bootstrap",
+                "--topic",
+                "graph topic",
+                "--preview",
+                "--topic-commit-limit",
+                "2",
+            ]
+        )
+
+    assert exit_code == 0
+    _, kwargs = mocked_bootstrap.call_args
+    assert kwargs["preview_only"] is True
+    assert kwargs["topic_commit_limit"] == 2
+
+
+def test_cli_bootstrap_accepts_stored_topic_metadata(tmp_path):
+    from unittest.mock import patch
+
+    database = tmp_path / "library.sqlite3"
+    with patch("citegeist.cli.Bootstrapper.bootstrap") as mocked_bootstrap:
+        mocked_bootstrap.return_value = []
+        exit_code = main(
+            [
+                "--db",
+                str(database),
+                "bootstrap",
+                "--topic",
+                "graph topic",
+                "--topic-slug",
+                "graph-methods",
+                "--topic-name",
+                "Graph Methods",
+                "--store-topic-phrase",
+                "graph networks biology",
+            ]
+        )
+
+    assert exit_code == 0
+    _, kwargs = mocked_bootstrap.call_args
+    assert kwargs["topic_slug"] == "graph-methods"
+    assert kwargs["topic_name"] == "Graph Methods"
+    assert kwargs["topic_phrase"] == "graph networks biology"
+
+
+def test_cli_scrape_talkorigins_accepts_output_dir(tmp_path):
+    from unittest.mock import patch
+
+    database = tmp_path / "library.sqlite3"
+    with patch("citegeist.cli.TalkOriginsScraper.scrape_to_directory") as mocked_scrape:
+        mocked_scrape.return_value = __import__("citegeist").TalkOriginsBatchExport(
+            base_url="https://www.talkorigins.org/origins/biblio/",
+            output_dir=str(tmp_path),
+            topic_count=1,
+            entry_count=2,
+            jobs_path=str(tmp_path / "jobs.json"),
+            manifest_path=str(tmp_path / "manifest.json"),
+            seed_sets=[],
+        )
+        exit_code = main(
+            [
+                "--db",
+                str(database),
+                "scrape-talkorigins",
+                str(tmp_path / "talkorigins-out"),
+                "--limit-topics",
+                "3",
+                "--limit-entries-per-topic",
+                "10",
+                "--no-resume",
+                "--no-expand",
+            ]
+        )
+
+    assert exit_code == 0
+
+
+def test_cli_validate_talkorigins_accepts_manifest(tmp_path):
+    from unittest.mock import patch
+
+    manifest = tmp_path / "talkorigins_manifest.json"
+    manifest.write_text("{}", encoding="utf-8")
+    with patch("citegeist.cli.TalkOriginsScraper.validate_export") as mocked_validate:
+        mocked_validate.return_value = __import__("citegeist").TalkOriginsValidationReport(
+            manifest_path=str(manifest),
+            topic_count=1,
+            entry_count=2,
+            parsed_ratio=1.0,
+            missing_author_count=0,
+            missing_title_count=0,
+            missing_year_count=0,
+            suspicious_entry_type_count=0,
+            suspicious_examples=[],
+            duplicate_cluster_count=0,
+            duplicate_entry_count=0,
+            duplicate_examples=[],
+        )
+        exit_code = main(["validate-talkorigins", str(manifest)])
+
+    assert exit_code == 0
+
+
+def test_cli_suggest_talkorigins_phrases_writes_output(tmp_path):
+    from unittest.mock import patch
+
+    manifest = tmp_path / "talkorigins_manifest.json"
+    manifest.write_text("{}", encoding="utf-8")
+    output = tmp_path / "phrases.json"
+    with patch("citegeist.cli.TalkOriginsScraper.suggest_topic_phrases") as mocked_suggest:
+        mocked_suggest.return_value = [
+            __import__("citegeist", fromlist=["TalkOriginsTopicPhraseSuggestion"]).TalkOriginsTopicPhraseSuggestion(
+                slug="abiogenesis",
+                topic="Abiogenesis",
+                entry_count=2,
+                suggested_phrase="Abiogenesis prebiotic chemistry ribozyme",
+                keywords=["prebiotic", "chemistry", "ribozyme"],
+                review_required=True,
+                review_reasons=["small_topic"],
+            )
+        ]
+        exit_code = main(
+            [
+                "suggest-talkorigins-phrases",
+                str(manifest),
+                "--topic",
+                "abiogenesis",
+                "--output",
+                str(output),
+            ]
+        )
+
+    assert exit_code == 0
+    payload = json.loads(output.read_text(encoding="utf-8"))
+    assert payload[0]["slug"] == "abiogenesis"
+
+
+def test_cli_duplicates_talkorigins_accepts_manifest(tmp_path):
+    from unittest.mock import patch
+
+    manifest = tmp_path / "talkorigins_manifest.json"
+    manifest.write_text("{}", encoding="utf-8")
+    with patch("citegeist.cli.TalkOriginsScraper.inspect_duplicate_clusters") as mocked_duplicates:
+        mocked_duplicates.return_value = [
+            __import__("citegeist.talkorigins", fromlist=["TalkOriginsDuplicateCluster"]).TalkOriginsDuplicateCluster(
+                key="smith|1999|duplicate paper",
+                count=2,
+                items=[
+                    {
+                        "citation_key": "dup1",
+                        "title": "Duplicate Paper",
+                        "author": "Smith, Jane",
+                        "year": "1999",
+                        "seed_bib": "a.bib",
+                        "topic": "Abiogenesis",
+                        "topic_slug": "abiogenesis",
+                    }
+                ],
+                canonical={
+                    "citation_key": "dup1",
+                    "entry_type": "article",
+                    "field_count": 3,
+                    "fields": {"title": "Duplicate Paper"},
+                    "weak_reasons": [],
+                },
+            )
+        ]
+        exit_code = main(
+            [
+                "duplicates-talkorigins",
+                str(manifest),
+                "--topic",
+                "abiogenesis",
+                "--match",
+                "duplicate",
+                "--preview",
+                "--weak-only",
+            ]
+        )
+
+    assert exit_code == 0
+
+
+def test_cli_ingest_talkorigins_accepts_manifest(tmp_path):
+    from unittest.mock import patch
+
+    database = tmp_path / "library.sqlite3"
+    manifest = tmp_path / "talkorigins_manifest.json"
+    manifest.write_text("{}", encoding="utf-8")
+    with patch("citegeist.cli.TalkOriginsScraper.ingest_export") as mocked_ingest:
+        mocked_ingest.return_value = __import__("citegeist").TalkOriginsIngestReport(
+            manifest_path=str(manifest),
+            topic_count=1,
+            raw_entry_count=2,
+            stored_entry_count=1,
+            duplicate_cluster_count=1,
+            duplicate_entry_count=2,
+            canonicalized_count=1,
+        )
+        exit_code = main(["--db", str(database), "ingest-talkorigins", str(manifest)])
+
+    assert exit_code == 0
+
+
+def test_cli_enrich_talkorigins_accepts_manifest(tmp_path):
+    from unittest.mock import patch
+
+    database = tmp_path / "library.sqlite3"
+    manifest = tmp_path / "talkorigins_manifest.json"
+    manifest.write_text("{}", encoding="utf-8")
+    with patch("citegeist.cli.TalkOriginsScraper.enrich_weak_canonicals") as mocked_enrich:
+        mocked_enrich.return_value = [
+            __import__("citegeist.talkorigins", fromlist=["TalkOriginsEnrichmentResult"]).TalkOriginsEnrichmentResult(
+                key="smith|1999|duplicate paper",
+                citation_key="dup1",
+                weak_reasons_before=["missing:doi"],
+                resolved=True,
+                applied=False,
+                source_label="crossref:search:Duplicate Paper",
+                weak_reasons_after=[],
+                conflicts=[],
+                error="",
+            )
+        ]
+        exit_code = main(
+            [
+                "--db",
+                str(database),
+                "enrich-talkorigins",
+                str(manifest),
+                "--limit",
+                "5",
+                "--apply",
+                "--allow-unsafe-search-matches",
+            ]
+        )
+
+    assert exit_code == 0
+
+
+def test_cli_review_talkorigins_writes_output(tmp_path):
+    from unittest.mock import patch
+
+    database = tmp_path / "library.sqlite3"
+    manifest = tmp_path / "talkorigins_manifest.json"
+    manifest.write_text("{}", encoding="utf-8")
+    output = tmp_path / "review.json"
+    with patch("citegeist.cli.TalkOriginsScraper.build_review_export") as mocked_review:
+        mocked_review.return_value = __import__("citegeist.talkorigins", fromlist=["TalkOriginsReviewExport"]).TalkOriginsReviewExport(
+            manifest_path=str(manifest),
+            item_count=1,
+            items=[{"key": "smith|1999|duplicate paper", "canonical": {}, "enrichment": {}}],
+        )
+        exit_code = main(
+            [
+                "--db",
+                str(database),
+                "review-talkorigins",
+                str(manifest),
+                "--output",
+                str(output),
+            ]
+        )
+
+    assert exit_code == 0
+    assert output.exists()
+
+
+def test_cli_apply_talkorigins_corrections_accepts_files(tmp_path):
+    from unittest.mock import patch
+
+    database = tmp_path / "library.sqlite3"
+    manifest = tmp_path / "talkorigins_manifest.json"
+    corrections = tmp_path / "corrections.json"
+    manifest.write_text("{}", encoding="utf-8")
+    corrections.write_text('{"corrections": []}', encoding="utf-8")
+    with patch("citegeist.cli.TalkOriginsScraper.apply_review_corrections") as mocked_apply:
+        mocked_apply.return_value = [
+            __import__("citegeist.talkorigins", fromlist=["TalkOriginsCorrectionResult"]).TalkOriginsCorrectionResult(
+                key="smith|1999|duplicate paper",
+                citation_key="dup1",
+                applied=True,
+                error="",
+            )
+        ]
+        exit_code = main(
+            [
+                "--db",
+                str(database),
+                "apply-talkorigins-corrections",
+                str(manifest),
+                str(corrections),
+            ]
+        )
+
+    assert exit_code == 0
+
+
+def test_cli_topics_and_topic_entries(tmp_path: Path):
+    bib_path = tmp_path / "input.bib"
+    bib_path.write_text(
+        """
+@article{seed2024,
+  author = {Seed, Alice},
+  title = {Seed Paper},
+  year = {2024}
+}
+""",
+        encoding="utf-8",
+    )
+    ingest = run_cli(tmp_path, "ingest", str(bib_path))
+    assert ingest.returncode == 0
+
+    from citegeist.storage import BibliographyStore
+
+    database = tmp_path / "library.sqlite3"
+    store = BibliographyStore(database)
+    try:
+        store.add_entry_topic(
+            "seed2024",
+            topic_slug="graph-methods",
+            topic_name="Graph Methods",
+            source_type="talkorigins",
+            source_url="https://example.org/topics/graph-methods",
+            source_label="topic-seed",
+        )
+        store.connection.commit()
+    finally:
+        store.close()
+
+    topics = run_cli(tmp_path, "topics")
+    assert topics.returncode == 0
+    topics_payload = json.loads(topics.stdout)
+    assert topics_payload[0]["slug"] == "graph-methods"
+
+    topic_entries = run_cli(tmp_path, "topic-entries", "graph-methods")
+    assert topic_entries.returncode == 0
+    topic_payload = json.loads(topic_entries.stdout)
+    assert topic_payload["topic"]["slug"] == "graph-methods"
+    assert topic_payload["entries"][0]["citation_key"] == "seed2024"
+
+
+def test_cli_can_set_topic_phrase(tmp_path: Path):
+    bib_path = tmp_path / "input.bib"
+    bib_path.write_text(
+        """
+@article{seed2024,
+  author = {Seed, Alice},
+  title = {Seed Paper},
+  year = {2024}
+}
+""",
+        encoding="utf-8",
+    )
+    ingest = run_cli(tmp_path, "ingest", str(bib_path))
+    assert ingest.returncode == 0
+
+    from citegeist.storage import BibliographyStore
+
+    database = tmp_path / "library.sqlite3"
+    store = BibliographyStore(database)
+    try:
+        store.add_entry_topic(
+            "seed2024",
+            topic_slug="graph-methods",
+            topic_name="Graph Methods",
+            source_type="talkorigins",
+            source_url="https://example.org/topics/graph-methods",
+            source_label="topic-seed",
+        )
+        store.connection.commit()
+    finally:
+        store.close()
+
+    result = run_cli(tmp_path, "set-topic-phrase", "graph-methods", "graph networks biology")
+    assert result.returncode == 0
+    payload = json.loads(result.stdout)
+    assert payload["expansion_phrase"] == "graph networks biology"
+
+
+def test_cli_can_apply_topic_phrases_from_json(tmp_path: Path):
+    bib_path = tmp_path / "input.bib"
+    bib_path.write_text(
+        """
+@article{seed2024,
+  author = {Seed, Alice},
+  title = {Seed Paper},
+  year = {2024}
+}
+""",
+        encoding="utf-8",
+    )
+    ingest = run_cli(tmp_path, "ingest", str(bib_path))
+    assert ingest.returncode == 0
+
+    from citegeist.storage import BibliographyStore
+
+    database = tmp_path / "library.sqlite3"
+    store = BibliographyStore(database)
+    try:
+        store.add_entry_topic(
+            "seed2024",
+            topic_slug="graph-methods",
+            topic_name="Graph Methods",
+            source_type="talkorigins",
+            source_url="https://example.org/topics/graph-methods",
+            source_label="topic-seed",
+        )
+        store.connection.commit()
+    finally:
+        store.close()
+
+    phrases_path = tmp_path / "phrases.json"
+    phrases_path.write_text(
+        json.dumps(
+            [
+                {
+                    "slug": "graph-methods",
+                    "suggested_phrase": "graph networks biology",
+                }
+            ]
+        ),
+        encoding="utf-8",
+    )
+
+    result = run_cli(tmp_path, "apply-topic-phrases", str(phrases_path))
+    assert result.returncode == 0
+    payload = json.loads(result.stdout)
+    assert payload[0]["applied"] is True
+
+    check = run_cli(tmp_path, "topics")
+    topics_payload = json.loads(check.stdout)
+    assert topics_payload[0]["expansion_phrase"] == "graph networks biology"
+
+
+def test_cli_can_stage_topic_phrases_from_json(tmp_path: Path):
+    bib_path = tmp_path / "input.bib"
+    bib_path.write_text(
+        """
+@article{seed2024,
+  author = {Seed, Alice},
+  title = {Seed Paper},
+  year = {2024}
+}
+""",
+        encoding="utf-8",
+    )
+    ingest = run_cli(tmp_path, "ingest", str(bib_path))
+    assert ingest.returncode == 0
+
+    from citegeist.storage import BibliographyStore
+
+    database = tmp_path / "library.sqlite3"
+    store = BibliographyStore(database)
+    try:
+        store.add_entry_topic(
+            "seed2024",
+            topic_slug="graph-methods",
+            topic_name="Graph Methods",
+            source_type="talkorigins",
+            source_url="https://example.org/topics/graph-methods",
+            source_label="topic-seed",
+        )
+        store.connection.commit()
+    finally:
+        store.close()
+
+    phrases_path = tmp_path / "phrases.json"
+    phrases_path.write_text(
+        json.dumps(
+            [
+                {
+                    "slug": "graph-methods",
+                    "suggested_phrase": "graph networks biology",
+                }
+            ]
+        ),
+        encoding="utf-8",
+    )
+
+    result = run_cli(tmp_path, "stage-topic-phrases", str(phrases_path))
+    assert result.returncode == 0
+    payload = json.loads(result.stdout)
+    assert payload[0]["staged"] is True
+    assert payload[0]["phrase_review_status"] == "pending"
+
+    check = run_cli(tmp_path, "topics")
+    topics_payload = json.loads(check.stdout)
+    assert topics_payload[0]["suggested_phrase"] == "graph networks biology"
+    assert topics_payload[0]["expansion_phrase"] is None
+    assert topics_payload[0]["phrase_review_status"] == "pending"
+
+
+def test_cli_can_review_topic_phrase(tmp_path: Path):
+    bib_path = tmp_path / "input.bib"
+    bib_path.write_text(
+        """
+@article{seed2024,
+  author = {Seed, Alice},
+  title = {Seed Paper},
+  year = {2024}
+}
+""",
+        encoding="utf-8",
+    )
+    ingest = run_cli(tmp_path, "ingest", str(bib_path))
+    assert ingest.returncode == 0
+
+    from citegeist.storage import BibliographyStore
+
+    database = tmp_path / "library.sqlite3"
+    store = BibliographyStore(database)
+    try:
+        store.add_entry_topic(
+            "seed2024",
+            topic_slug="graph-methods",
+            topic_name="Graph Methods",
+            source_type="talkorigins",
+            source_url="https://example.org/topics/graph-methods",
+            source_label="topic-seed",
+        )
+        store.stage_topic_phrase_suggestion("graph-methods", "graph networks biology")
+    finally:
+        store.close()
+
+    result = run_cli(
+        tmp_path,
+        "review-topic-phrase",
+        "graph-methods",
+        "accepted",
+        "--notes",
+        "curated and approved",
+    )
+    assert result.returncode == 0
+    payload = json.loads(result.stdout)
+    assert payload["suggested_phrase"] == "graph networks biology"
+    assert payload["expansion_phrase"] == "graph networks biology"
+    assert payload["phrase_review_status"] == "accepted"
+    assert payload["phrase_review_notes"] == "curated and approved"
+
+
+def test_cli_topics_can_filter_by_phrase_review_status(tmp_path: Path):
+    bib_path = tmp_path / "input.bib"
+    bib_path.write_text(
+        """
+@article{seed2024,
+  author = {Seed, Alice},
+  title = {Seed Paper},
+  year = {2024}
+}
+""",
+        encoding="utf-8",
+    )
+    ingest = run_cli(tmp_path, "ingest", str(bib_path))
+    assert ingest.returncode == 0
+
+    from citegeist.storage import BibliographyStore
+
+    database = tmp_path / "library.sqlite3"
+    store = BibliographyStore(database)
+    try:
+        store.add_entry_topic(
+            "seed2024",
+            topic_slug="graph-methods",
+            topic_name="Graph Methods",
+            source_type="talkorigins",
+            source_url="https://example.org/topics/graph-methods",
+            source_label="topic-seed",
+        )
+        store.ensure_topic("abiogenesis", "Abiogenesis")
+        store.stage_topic_phrase_suggestion("graph-methods", "graph networks biology")
+        store.stage_topic_phrase_suggestion("abiogenesis", "abiogenesis life origin")
+        store.review_topic_phrase_suggestion("abiogenesis", "accepted")
+    finally:
+        store.close()
+
+    result = run_cli(tmp_path, "topics", "--phrase-review-status", "pending")
+    assert result.returncode == 0
+    payload = json.loads(result.stdout)
+    assert [topic["slug"] for topic in payload] == ["graph-methods"]
+
+
+def test_cli_export_topic(tmp_path: Path):
+    bib_path = tmp_path / "input.bib"
+    bib_path.write_text(
+        """
+@article{seed2024,
+  author = {Seed, Alice},
+  title = {Seed Paper},
+  year = {2024}
+}
+""",
+        encoding="utf-8",
+    )
+    ingest = run_cli(tmp_path, "ingest", str(bib_path))
+    assert ingest.returncode == 0
+
+    from citegeist.storage import BibliographyStore
+
+    database = tmp_path / "library.sqlite3"
+    store = BibliographyStore(database)
+    try:
+        store.add_entry_topic(
+            "seed2024",
+            topic_slug="graph-methods",
+            topic_name="Graph Methods",
+            source_type="talkorigins",
+            source_url="https://example.org/topics/graph-methods",
+            source_label="topic-seed",
+        )
+        store.connection.commit()
+    finally:
+        store.close()
+
+    export_path = tmp_path / "graph-methods.bib"
+    result = run_cli(tmp_path, "export-topic", "graph-methods", "--output", str(export_path))
+    assert result.returncode == 0
+    exported = export_path.read_text(encoding="utf-8")
+    assert "@article{seed2024," in exported
+
+
+def test_cli_search_can_filter_by_topic(tmp_path: Path):
+    bib_path = tmp_path / "input.bib"
+    bib_path.write_text(
+        """
+@article{seed2024,
+  author = {Seed, Alice},
+  title = {Graph Methods for Biology},
+  year = {2024},
+  abstract = {A graph methods paper.}
+}
+
+@article{other2023,
+  author = {Other, Bob},
+  title = {Graph Methods for Chemistry},
+  year = {2023},
+  abstract = {Another graph methods paper.}
+}
+""",
+        encoding="utf-8",
+    )
+    ingest = run_cli(tmp_path, "ingest", str(bib_path))
+    assert ingest.returncode == 0
+
+    from citegeist.storage import BibliographyStore
+
+    database = tmp_path / "library.sqlite3"
+    store = BibliographyStore(database)
+    try:
+        store.add_entry_topic(
+            "seed2024",
+            topic_slug="biology",
+            topic_name="Biology",
+            source_type="talkorigins",
+            source_url="https://example.org/topics/biology",
+            source_label="topic-seed",
+        )
+        store.add_entry_topic(
+            "other2023",
+            topic_slug="chemistry",
+            topic_name="Chemistry",
+            source_type="talkorigins",
+            source_url="https://example.org/topics/chemistry",
+            source_label="topic-seed",
+        )
+        store.connection.commit()
+    finally:
+        store.close()
+
+    search = run_cli(tmp_path, "search", "graph", "--topic", "biology")
+    assert search.returncode == 0
+    assert "seed2024" in search.stdout
+    assert "other2023" not in search.stdout
 
 
 def test_cli_graph_outputs_missing_targets(tmp_path: Path):
@@ -239,3 +1036,43 @@ def test_cli_expand_with_mocked_openalex(tmp_path: Path):
         )
 
     assert exit_code == 0
+
+
+def test_cli_expand_topic_with_mocked_expander(tmp_path: Path):
+    from citegeist.expand import TopicExpansionResult
+
+    with patch("citegeist.cli.TopicExpander.expand_topic") as mocked_expand:
+        mocked_expand.return_value = [
+            TopicExpansionResult(
+                topic_slug="abiogenesis",
+                source_citation_key="seed2024",
+                discovered_citation_key="discovered1",
+                discovered_title="Abiogenesis origin chemistry",
+                created_entry=True,
+                relation_type="cites",
+                source_label="openalex:cites:seed2024",
+                relevance_score=0.67,
+                meets_relevance_threshold=True,
+                assigned_to_topic=True,
+            )
+        ]
+        database = tmp_path / "library.sqlite3"
+        exit_code = main(
+            [
+                "--db",
+                str(database),
+                "expand-topic",
+                "abiogenesis",
+                "--topic-phrase",
+                "abiogenesis origin chemistry",
+                "--seed-key",
+                "seed2024",
+                "--min-relevance",
+                "0.3",
+                "--preview",
+            ]
+        )
+
+    assert exit_code == 0
+    _, kwargs = mocked_expand.call_args
+    assert kwargs["preview_only"] is True

tests/test_harvest.py

@@ -0,0 +1,293 @@
+from citegeist import OaiPmhHarvester, parse_bibtex
+from citegeist.cli import main
+
+
+OAI_XML = """<?xml version="1.0" encoding="UTF-8"?>
+<OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/"
+         xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"
+         xmlns:dc="http://purl.org/dc/elements/1.1/">
+  <ListRecords>
+    <record>
+      <header>
+        <identifier>oai:example.edu:123</identifier>
+      </header>
+      <metadata>
+        <oai_dc:dc>
+          <dc:title>Thesis Metadata Harvesting</dc:title>
+          <dc:creator>Doe, Jane</dc:creator>
+          <dc:date>2023-05-01</dc:date>
+          <dc:description>A dissertation about repository harvesting.</dc:description>
+          <dc:identifier>https://example.edu/items/123</dc:identifier>
+          <dc:publisher>Example University</dc:publisher>
+          <dc:type>Text</dc:type>
+          <dc:type>Dissertation</dc:type>
+        </oai_dc:dc>
+      </metadata>
+    </record>
+  </ListRecords>
+</OAI-PMH>
+"""
+
+OAI_XML_PAGE_1 = """<?xml version="1.0" encoding="UTF-8"?>
+<OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/"
+         xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"
+         xmlns:dc="http://purl.org/dc/elements/1.1/">
+  <ListRecords>
+    <record>
+      <header>
+        <identifier>oai:example.edu:123</identifier>
+      </header>
+      <metadata>
+        <oai_dc:dc>
+          <dc:title>First Harvested Thesis</dc:title>
+          <dc:creator>Doe, Jane</dc:creator>
+          <dc:date>2023-05-01</dc:date>
+          <dc:type>Dissertation</dc:type>
+        </oai_dc:dc>
+      </metadata>
+    </record>
+    <resumptionToken>TOKEN123</resumptionToken>
+  </ListRecords>
+</OAI-PMH>
+"""
+
+OAI_XML_PAGE_2 = """<?xml version="1.0" encoding="UTF-8"?>
+<OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/"
+         xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"
+         xmlns:dc="http://purl.org/dc/elements/1.1/">
+  <ListRecords>
+    <record>
+      <header>
+        <identifier>oai:example.edu:456</identifier>
+      </header>
+      <metadata>
+        <oai_dc:dc>
+          <dc:title>Second Harvested Thesis</dc:title>
+          <dc:creator>Smith, John</dc:creator>
+          <dc:date>2022-05-01</dc:date>
+          <dc:type>Dissertation</dc:type>
+        </oai_dc:dc>
+      </metadata>
+    </record>
+  </ListRecords>
+</OAI-PMH>
+"""
+
+OAI_IDENTIFY_XML = """<?xml version="1.0" encoding="UTF-8"?>
+<OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/">
+  <Identify>
+    <repositoryName>Example Repository</repositoryName>
+    <baseURL>https://example.edu/oai</baseURL>
+    <protocolVersion>2.0</protocolVersion>
+    <adminEmail>repo@example.edu</adminEmail>
+    <earliestDatestamp>2001-01-01</earliestDatestamp>
+    <deletedRecord>persistent</deletedRecord>
+    <granularity>YYYY-MM-DD</granularity>
+  </Identify>
+</OAI-PMH>
+"""
+
+OAI_LISTSETS_XML = """<?xml version="1.0" encoding="UTF-8"?>
+<OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/">
+  <ListSets>
+    <set>
+      <setSpec>theses</setSpec>
+      <setName>Theses and Dissertations</setName>
+      <setDescription>
+        <description>This set contains graduate theses.</description>
+      </setDescription>
+    </set>
+  </ListSets>
+</OAI-PMH>
+"""
+
+OAI_METADATA_FORMATS_XML = """<?xml version="1.0" encoding="UTF-8"?>
+<OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/">
+  <ListMetadataFormats>
+    <metadataFormat>
+      <metadataPrefix>oai_dc</metadataPrefix>
+      <schema>http://www.openarchives.org/OAI/2.0/oai_dc.xsd</schema>
+      <metadataNamespace>http://www.openarchives.org/OAI/2.0/oai_dc/</metadataNamespace>
+    </metadataFormat>
+    <metadataFormat>
+      <metadataPrefix>mods</metadataPrefix>
+      <schema>http://www.loc.gov/standards/mods/v3/mods-3-7.xsd</schema>
+      <metadataNamespace>http://www.loc.gov/mods/v3</metadataNamespace>
+    </metadataFormat>
+  </ListMetadataFormats>
+</OAI-PMH>
+"""
+
+OAI_MODS_XML = """<?xml version="1.0" encoding="UTF-8"?>
+<OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/"
+         xmlns:mods="http://www.loc.gov/mods/v3">
+  <ListRecords>
+    <record>
+      <header>
+        <identifier>oai:example.edu:mods123</identifier>
+      </header>
+      <metadata>
+        <mods:mods>
+          <mods:titleInfo>
+            <mods:title>MODS Thesis Title</mods:title>
+          </mods:titleInfo>
+          <mods:name>
+            <mods:namePart>Doe</mods:namePart>
+            <mods:namePart>Jane</mods:namePart>
+            <mods:role>
+              <mods:roleTerm>author</mods:roleTerm>
+            </mods:role>
+          </mods:name>
+          <mods:originInfo>
+            <mods:publisher>Example University</mods:publisher>
+            <mods:dateIssued>2022</mods:dateIssued>
+          </mods:originInfo>
+          <mods:genre>dissertation</mods:genre>
+          <mods:abstract>MODS abstract text.</mods:abstract>
+          <mods:location>
+            <mods:url>https://example.edu/mods123</mods:url>
+          </mods:location>
+        </mods:mods>
+      </metadata>
+    </record>
+  </ListRecords>
+</OAI-PMH>
+"""
+
+
+def test_oai_harvester_maps_dublin_core_to_bibentry():
+    harvester = OaiPmhHarvester()
+    harvester.source_client.get_xml = lambda _url: __import__("xml.etree.ElementTree").etree.ElementTree.fromstring(OAI_XML)  # type: ignore[method-assign]
+
+    results = harvester.list_records("https://example.edu/oai")
+
+    assert len(results) == 1
+    entry = results[0].entry
+    assert entry.entry_type == "phdthesis"
+    assert entry.fields["title"] == "Thesis Metadata Harvesting"
+    assert entry.fields["author"] == "Doe, Jane"
+    assert entry.fields["oai"] == "oai:example.edu:123"
+
+
+def test_oai_harvester_follows_resumption_tokens():
+    harvester = OaiPmhHarvester()
+    from xml.etree import ElementTree as ET
+
+    payloads = iter([ET.fromstring(OAI_XML_PAGE_1), ET.fromstring(OAI_XML_PAGE_2)])
+    harvester.source_client.get_xml = lambda _url: next(payloads)  # type: ignore[method-assign]
+
+    results = harvester.list_records("https://example.edu/oai")
+
+    assert [result.identifier for result in results] == [
+        "oai:example.edu:123",
+        "oai:example.edu:456",
+    ]
+    assert [result.entry.citation_key for result in results] == [
+        "doe2023first1",
+        "smith2022second2",
+    ]
+
+
+def test_oai_harvester_passes_date_filters():
+    harvester = OaiPmhHarvester()
+    seen_urls: list[str] = []
+    from xml.etree import ElementTree as ET
+
+    def fake_get_xml(url: str):
+        seen_urls.append(url)
+        return ET.fromstring(OAI_XML)
+
+    harvester.source_client.get_xml = fake_get_xml  # type: ignore[method-assign]
+
+    harvester.list_records(
+        "https://example.edu/oai",
+        date_from="2023-01-01",
+        date_until="2023-12-31",
+        limit=1,
+    )
+
+    assert "from=2023-01-01" in seen_urls[0]
+    assert "until=2023-12-31" in seen_urls[0]
+
+
+def test_oai_harvester_maps_mods_records():
+    harvester = OaiPmhHarvester()
+    from xml.etree import ElementTree as ET
+
+    harvester.source_client.get_xml = lambda _url: ET.fromstring(OAI_MODS_XML)  # type: ignore[method-assign]
+
+    results = harvester.list_records("https://example.edu/oai", metadata_prefix="mods")
+
+    assert len(results) == 1
+    entry = results[0].entry
+    assert entry.entry_type == "phdthesis"
+    assert entry.fields["title"] == "MODS Thesis Title"
+    assert entry.fields["author"] == "Doe, Jane"
+    assert entry.fields["publisher"] == "Example University"
+    assert entry.fields["abstract"] == "MODS abstract text."
+
+
+def test_oai_harvester_can_identify_repository_and_list_sets():
+    harvester = OaiPmhHarvester()
+    from xml.etree import ElementTree as ET
+
+    payloads = iter(
+        [ET.fromstring(OAI_IDENTIFY_XML), ET.fromstring(OAI_LISTSETS_XML), ET.fromstring(OAI_METADATA_FORMATS_XML)]
+    )
+    harvester.source_client.get_xml = lambda _url: next(payloads)  # type: ignore[method-assign]
+
+    identify = harvester.identify("https://example.edu/oai")
+    sets = harvester.list_sets("https://example.edu/oai")
+    formats = harvester.list_metadata_formats("https://example.edu/oai")
+
+    assert identify["repositoryName"] == "Example Repository"
+    assert identify["granularity"] == "YYYY-MM-DD"
+    assert sets[0].set_spec == "theses"
+    assert sets[0].set_name == "Theses and Dissertations"
+    assert "graduate theses" in sets[0].set_description
+    assert [item.metadata_prefix for item in formats] == ["oai_dc", "mods"]
+
+
+def test_harvest_oai_cli_ingests_records(tmp_path):
+    from unittest.mock import patch
+
+    database = tmp_path / "library.sqlite3"
+    harvester = OaiPmhHarvester()
+    from xml.etree import ElementTree as ET
+
+    harvester.source_client.get_xml = lambda _url: ET.fromstring(OAI_XML)  # type: ignore[method-assign]
+    harvested = harvester.list_records("https://example.edu/oai")
+
+    with patch("citegeist.cli.OaiPmhHarvester.list_records") as mocked_list:
+        mocked_list.return_value = harvested
+
+        exit_code = main(
+            [
+                "--db",
+                str(database),
+                "harvest-oai",
+                "https://example.edu/oai",
+                "--metadata-prefix",
+                "oai_dc",
+                "--from",
+                "2023-01-01",
+                "--until",
+                "2023-12-31",
+                "--limit",
+                "5",
+            ]
+        )
+
+    assert exit_code == 0
+
+    from citegeist.storage import BibliographyStore
+
+    store = BibliographyStore(database)
+    try:
+        entry = store.list_entries(limit=10)[0]
+        assert entry["citation_key"] == "doe2023thesis1"
+        bibtex = store.get_entry_bibtex("doe2023thesis1")
+        parsed = parse_bibtex(bibtex or "")
+        assert parsed[0].fields["oai"] == "oai:example.edu:123"
+    finally:
+        store.close()

tests/test_resolve.py

@@ -1,11 +1,13 @@
 from xml.etree import ElementTree as ET
 
-from citegeist.bibtex import BibEntry
+from citegeist.bibtex import BibEntry, render_bibtex
 from citegeist.resolve import (
     MetadataResolver,
     _arxiv_atom_entry_to_bib,
     _crossref_message_to_entry,
+    _datacite_work_to_entry,
     _openalex_work_to_entry,
+    merge_entries_with_conflicts,
     merge_entries,
 )
 
@@ -65,6 +67,31 @@ def test_merge_entries_prefers_existing_values_and_adds_missing_fields():
     assert merged.fields["journal"] == "Journal of Graph Studies"
 
 
+def test_merge_entries_with_conflicts_records_disagreements():
+    base = BibEntry(
+        entry_type="article",
+        citation_key="smith2024graphs",
+        fields={"title": "Existing Title", "journal": "Current Journal"},
+    )
+    resolved = BibEntry(
+        entry_type="article",
+        citation_key="resolved",
+        fields={"title": "Resolved Title", "journal": "Current Journal", "year": "2024"},
+    )
+
+    merged, conflicts = merge_entries_with_conflicts(base, resolved)
+
+    assert merged.fields["title"] == "Existing Title"
+    assert merged.fields["year"] == "2024"
+    assert conflicts == [
+        {
+            "field_name": "title",
+            "current_value": "Existing Title",
+            "proposed_value": "Resolved Title",
+        }
+    ]
+
+
 def test_resolver_tries_doi_before_dblp():
     resolver = MetadataResolver()
     calls: list[tuple[str, str]] = []
@@ -77,7 +104,12 @@ def test_resolver_tries_doi_before_dblp():
         calls.append(("dblp", value))
         return None
 
+    def fake_datacite(value: str):
+        calls.append(("datacite", value))
+        return None
+
     resolver.resolve_doi = fake_doi  # type: ignore[method-assign]
+    resolver.resolve_datacite_doi = fake_datacite  # type: ignore[method-assign]
     resolver.resolve_dblp = fake_dblp  # type: ignore[method-assign]
 
     resolver.resolve_entry(
@@ -88,7 +120,11 @@ def test_resolver_tries_doi_before_dblp():
         )
     )
 
-    assert calls == [("doi", "10.1000/example-doi"), ("dblp", "conf/test/Smith24")]
+    assert calls == [
+        ("doi", "10.1000/example-doi"),
+        ("datacite", "10.1000/example-doi"),
+        ("dblp", "conf/test/Smith24"),
+    ]
 
 
 def test_openalex_work_to_entry_maps_basic_fields():
@@ -131,6 +167,8 @@ def test_resolver_can_resolve_openalex_id():
 
 def test_resolver_falls_back_to_openalex_title_search():
     resolver = MetadataResolver()
+    resolver.search_datacite = lambda title, limit=5: []  # type: ignore[method-assign]
+    resolver.search_crossref = lambda title, limit=5: []  # type: ignore[method-assign]
     resolver.search_openalex = lambda title, limit=5: [  # type: ignore[method-assign]
         _openalex_work_to_entry(
             {
@@ -154,3 +192,212 @@ def test_resolver_falls_back_to_openalex_title_search():
     assert resolution is not None
     assert resolution.source_label == "openalex:search:OpenAlex Resolved Work"
     assert resolution.entry.fields["openalex"] == "W12345"
+
+
+def test_resolver_prefers_exact_crossref_title_match_before_datacite():
+    resolver = MetadataResolver()
+    resolver.search_crossref = lambda title, limit=5: [  # type: ignore[method-assign]
+        _crossref_message_to_entry(
+            {
+                "type": "journal-article",
+                "title": [title],
+                "DOI": "10.1126/science.1090005",
+                "container-title": ["Science"],
+                "author": [
+                    {"family": "King", "given": "Mary-Claire"},
+                    {"family": "Wilson", "given": "A. C."},
+                ],
+                "issued": {"date-parts": [[1975, 4, 11]]},
+            }
+        )
+    ]
+    resolver.search_datacite = lambda title, limit=5: [  # type: ignore[method-assign]
+        _datacite_work_to_entry(
+            {
+                "attributes": {
+                    "doi": "10.5061/dryad.v6wwpzh17",
+                    "titles": [
+                        {
+                            "title": "Conserved patterns and locomotor-related evolutionary constraints in the hominoid vertebral column"
+                        }
+                    ],
+                    "creators": [
+                        {"familyName": "Villamil", "givenName": "Catalina I."},
+                        {"familyName": "Middleton", "givenName": "Emily R."},
+                    ],
+                    "publicationYear": 2024,
+                    "types": {"resourceTypeGeneral": "Dataset"},
+                }
+            }
+        )
+    ]
+
+    resolution = resolver.resolve_entry(
+        BibEntry(
+            entry_type="article",
+            citation_key="king1975evolution2",
+            fields={
+                "title": "Evolution at two levels in humans and chimpanzees",
+                "author": "King, M. C. and Wilson, A. C.",
+                "year": "1975",
+            },
+        )
+    )
+
+    assert resolution is not None
+    assert resolution.source_label == "crossref:search:Evolution at two levels in humans and chimpanzees"
+    assert resolution.entry.fields["doi"] == "10.1126/science.1090005"
+
+
+def test_resolver_rejects_mismatched_title_search_candidates():
+    resolver = MetadataResolver()
+    resolver.search_crossref = lambda title, limit=5: []  # type: ignore[method-assign]
+    resolver.search_datacite = lambda title, limit=5: [  # type: ignore[method-assign]
+        _datacite_work_to_entry(
+            {
+                "attributes": {
+                    "doi": "10.5061/dryad.v6wwpzh17",
+                    "titles": [
+                        {
+                            "title": "Conserved patterns and locomotor-related evolutionary constraints in the hominoid vertebral column"
+                        }
+                    ],
+                    "creators": [
+                        {"familyName": "Villamil", "givenName": "Catalina I."},
+                    ],
+                    "publicationYear": 2024,
+                    "types": {"resourceTypeGeneral": "Dataset"},
+                }
+            }
+        )
+    ]
+    resolver.search_openalex = lambda title, limit=5: [  # type: ignore[method-assign]
+        _openalex_work_to_entry(
+            {
+                "id": "https://openalex.org/W2033360601",
+                "display_name": "Immunological relatedness of glucose 6-phosphate dehydrogenases from vertebrate and invertebrate species.",
+                "publication_year": 1978,
+                "type": "article",
+                "authorships": [
+                    {"author": {"display_name": "Yoshikazu Sado"}},
+                    {"author": {"display_name": "Samuel H. Hori"}},
+                ],
+                "doi": "https://doi.org/10.1266/jjg.53.91",
+            }
+        )
+    ]
+
+    resolution = resolver.resolve_entry(
+        BibEntry(
+            entry_type="article",
+            citation_key="sarich1967immunological1",
+            fields={
+                "title": "Immunological Time Scale for Homonid Evolution",
+                "author": "Sarich, V. and Wilson, A.",
+                "year": "1967",
+            },
+        )
+    )
+
+    assert resolution is None
+
+
+def test_datacite_work_to_entry_maps_basic_fields():
+    entry = _datacite_work_to_entry(
+        {
+            "attributes": {
+                "doi": "10.1000/datacite-example",
+                "titles": [{"title": "Repository Dissertation Record"}],
+                "creators": [{"familyName": "Doe", "givenName": "Jane"}],
+                "publicationYear": 2021,
+                "publisher": "Example University",
+                "url": "https://example.edu/record/123",
+                "types": {"resourceTypeGeneral": "Dissertation"},
+                "descriptions": [
+                    {
+                        "descriptionType": "Abstract",
+                        "description": "An abstract from DataCite.",
+                    }
+                ],
+            }
+        }
+    )
+
+    assert entry.entry_type == "phdthesis"
+    assert entry.fields["doi"] == "10.1000/datacite-example"
+    assert entry.fields["author"] == "Doe, Jane"
+    assert entry.fields["publisher"] == "Example University"
+    assert entry.fields["abstract"] == "An abstract from DataCite."
+
+
+def test_resolver_can_resolve_datacite_doi():
+    resolver = MetadataResolver()
+    resolver.source_client.get_json = lambda _url: {  # type: ignore[method-assign]
+        "data": {
+            "attributes": {
+                "doi": "10.1000/datacite-example",
+                "titles": [{"title": "Repository Dissertation Record"}],
+                "creators": [{"familyName": "Doe", "givenName": "Jane"}],
+                "publicationYear": 2021,
+                "types": {"resourceTypeGeneral": "Dissertation"},
+            }
+        }
+    }
+
+    resolution = resolver.resolve_datacite_doi("10.1000/datacite-example")
+
+    assert resolution is not None
+    assert resolution.source_label == "datacite:doi:10.1000/datacite-example"
+    assert resolution.entry.entry_type == "phdthesis"
+
+
+def test_resolver_can_fall_back_to_datacite_title_search():
+    resolver = MetadataResolver()
+    resolver.search_crossref = lambda title, limit=5: []  # type: ignore[method-assign]
+    resolver.search_datacite = lambda title, limit=5: [  # type: ignore[method-assign]
+        _datacite_work_to_entry(
+            {
+                "attributes": {
+                    "doi": "10.1000/datacite-example",
+                    "titles": [{"title": title}],
+                    "creators": [{"familyName": "Doe", "givenName": "Jane"}],
+                    "publicationYear": 2021,
+                    "types": {"resourceTypeGeneral": "Dissertation"},
+                }
+            }
+        )
+    ]
+    resolver.search_openalex = lambda title, limit=5: []  # type: ignore[method-assign]
+
+    resolution = resolver.resolve_entry(
+        BibEntry(
+            entry_type="misc",
+            citation_key="draft1",
+            fields={"title": "Repository Dissertation Record", "author": "Doe, Jane", "year": "2021"},
+        )
+    )
+
+    assert resolution is not None
+    assert resolution.source_label == "datacite:search:Repository Dissertation Record"
+    assert resolution.entry.fields["doi"] == "10.1000/datacite-example"
+
+
+def test_render_bibtex_tolerates_unmatched_braces_in_field_values():
+    rendered = render_bibtex(
+        [
+            BibEntry(
+                entry_type="misc",
+                citation_key="broken2026",
+                fields={
+                    "author": "Broken, Example",
+                    "title": "Unmatched { braces } example } tail",
+                    "year": "2026",
+                    "note": "Open { brace only",
+                },
+            )
+        ]
+    )
+
+    assert "@misc{broken2026," in rendered
+    assert "Unmatched { braces } example ) tail" in rendered
+    assert "Open ( brace only" in rendered

tests/test_sources.py

@@ -28,3 +28,14 @@ def test_source_client_writes_cache_after_fetch(tmp_path: Path):
 
     assert payload["ok"] is True
     assert any(cache_dir.iterdir())
+
+
+def test_source_client_falls_back_to_latin1_for_text(tmp_path: Path):
+    client = SourceClient(cache_dir=tmp_path / "cache")
+    url = "https://example.org/latin1"
+
+    client._fetch_bytes = lambda _url: "café".encode("iso-8859-1")  # type: ignore[method-assign]
+
+    payload = client.get_text(url)
+
+    assert payload == "café"

tests/test_storage.py

@@ -130,3 +130,250 @@ def test_store_traverses_graph_and_surfaces_missing_targets():
         assert rows[2]["depth"] == 2
     finally:
         store.close()
+
+
+def test_store_records_and_updates_field_conflicts():
+    store = BibliographyStore()
+    try:
+        store.ingest_bibtex(
+            """
+@article{seed2024,
+  author = {Seed, Alice},
+  title = {Seed Paper},
+  year = {2024}
+}
+"""
+        )
+        ok = store.record_conflicts(
+            "seed2024",
+            [
+                {
+                    "field_name": "title",
+                    "current_value": "Seed Paper",
+                    "proposed_value": "Resolved Seed Paper",
+                }
+            ],
+            source_type="resolver",
+            source_label="crossref:doi:10.1000/seed",
+        )
+        assert ok is True
+        conflicts = store.get_field_conflicts("seed2024")
+        assert conflicts[0]["field_name"] == "title"
+        assert conflicts[0]["status"] == "open"
+        assert store.set_conflict_status("seed2024", "title", "accepted") == 1
+        updated = store.get_field_conflicts("seed2024", status="accepted")
+        assert len(updated) == 1
+    finally:
+        store.close()
+
+
+def test_store_can_apply_latest_conflict_value():
+    store = BibliographyStore()
+    try:
+        store.ingest_bibtex(
+            """
+@article{seed2024,
+  author = {Seed, Alice},
+  title = {Seed Paper},
+  year = {2024}
+}
+"""
+        )
+        store.record_conflicts(
+            "seed2024",
+            [
+                {
+                    "field_name": "title",
+                    "current_value": "Seed Paper",
+                    "proposed_value": "Resolved Seed Paper",
+                }
+            ],
+            source_type="resolver",
+            source_label="crossref:doi:10.1000/seed",
+        )
+
+        assert store.apply_conflict_value("seed2024", "title") is True
+        entry = store.get_entry("seed2024")
+        assert entry is not None
+        assert entry["title"] == "Resolved Seed Paper"
+        accepted = store.get_field_conflicts("seed2024", status="accepted")
+        assert len(accepted) == 1
+    finally:
+        store.close()
+
+
+def test_store_supports_entry_topic_membership():
+    store = BibliographyStore()
+    try:
+        store.ingest_bibtex(
+            """
+@article{seed2024,
+  author = {Seed, Alice},
+  title = {Seed Paper},
+  year = {2024}
+}
+"""
+        )
+
+        assert store.add_entry_topic(
+            "seed2024",
+            topic_slug="graph-methods",
+            topic_name="Graph Methods",
+            source_type="talkorigins",
+            source_url="https://example.org/topics/graph-methods",
+            source_label="topic-seed",
+        ) is True
+        assert store.add_entry_topic(
+            "seed2024",
+            topic_slug="semantic-search",
+            topic_name="Semantic Search",
+            source_type="talkorigins",
+            source_url="https://example.org/topics/semantic-search",
+            source_label="topic-seed",
+        ) is True
+
+        entry = store.get_entry("seed2024")
+        assert entry is not None
+        assert [topic["slug"] for topic in entry["topics"]] == ["graph-methods", "semantic-search"]
+
+        topics = store.list_topics()
+        assert [topic["slug"] for topic in topics] == ["graph-methods", "semantic-search"]
+        assert topics[0]["entry_count"] == 1
+        topic = store.get_topic("graph-methods")
+        assert topic is not None
+        assert topic["name"] == "Graph Methods"
+        assert topic["expansion_phrase"] is None
+        topic_entries = store.list_topic_entries("graph-methods")
+        assert topic_entries[0]["citation_key"] == "seed2024"
+    finally:
+        store.close()
+
+
+def test_store_can_set_topic_expansion_phrase():
+    store = BibliographyStore()
+    try:
+        store.ingest_bibtex(
+            """
+@article{seed2024,
+  author = {Seed, Alice},
+  title = {Seed Paper},
+  year = {2024}
+}
+"""
+        )
+        store.add_entry_topic(
+            "seed2024",
+            topic_slug="graph-methods",
+            topic_name="Graph Methods",
+            source_type="talkorigins",
+            source_url="https://example.org/topics/graph-methods",
+            source_label="topic-seed",
+        )
+        assert store.set_topic_expansion_phrase("graph-methods", "graph networks biology") is True
+
+        topic = store.get_topic("graph-methods")
+        assert topic is not None
+        assert topic["expansion_phrase"] == "graph networks biology"
+        assert topic["phrase_review_status"] == "unreviewed"
+        topics = store.list_topics()
+        assert topics[0]["expansion_phrase"] == "graph networks biology"
+    finally:
+        store.close()
+
+
+def test_store_can_stage_and_review_topic_phrase_suggestion():
+    store = BibliographyStore()
+    try:
+        store.ensure_topic("graph-methods", "Graph Methods")
+
+        assert store.stage_topic_phrase_suggestion(
+            "graph-methods",
+            "graph networks biology",
+            review_notes="generated from local titles",
+        ) is True
+
+        staged = store.get_topic("graph-methods")
+        assert staged is not None
+        assert staged["suggested_phrase"] == "graph networks biology"
+        assert staged["expansion_phrase"] is None
+        assert staged["phrase_review_status"] == "pending"
+        assert staged["phrase_review_notes"] == "generated from local titles"
+
+        assert store.review_topic_phrase_suggestion(
+            "graph-methods",
+            "accepted",
+            review_notes="looks good",
+        ) is True
+
+        reviewed = store.get_topic("graph-methods")
+        assert reviewed is not None
+        assert reviewed["suggested_phrase"] == "graph networks biology"
+        assert reviewed["expansion_phrase"] == "graph networks biology"
+        assert reviewed["phrase_review_status"] == "accepted"
+        assert reviewed["phrase_review_notes"] == "looks good"
+    finally:
+        store.close()
+
+
+def test_store_can_filter_topics_by_phrase_review_status():
+    store = BibliographyStore()
+    try:
+        store.ensure_topic("graph-methods", "Graph Methods")
+        store.ensure_topic("abiogenesis", "Abiogenesis")
+        store.stage_topic_phrase_suggestion("graph-methods", "graph networks biology")
+        store.stage_topic_phrase_suggestion("abiogenesis", "abiogenesis life origin")
+        store.review_topic_phrase_suggestion("abiogenesis", "accepted")
+
+        pending_topics = store.list_topics(phrase_review_status="pending")
+        accepted_topics = store.list_topics(phrase_review_status="accepted")
+
+        assert [topic["slug"] for topic in pending_topics] == ["graph-methods"]
+        assert [topic["slug"] for topic in accepted_topics] == ["abiogenesis"]
+    finally:
+        store.close()
+
+
+def test_store_search_text_can_filter_by_topic():
+    store = BibliographyStore()
+    try:
+        store.ingest_bibtex(
+            """
+@article{seed2024,
+  author = {Seed, Alice},
+  title = {Graph Methods for Biology},
+  year = {2024},
+  abstract = {A graph methods paper.}
+}
+
+@article{other2023,
+  author = {Other, Bob},
+  title = {Graph Methods for Chemistry},
+  year = {2023},
+  abstract = {Another graph methods paper.}
+}
+"""
+        )
+
+        store.add_entry_topic(
+            "seed2024",
+            topic_slug="biology",
+            topic_name="Biology",
+            source_type="talkorigins",
+            source_url="https://example.org/topics/biology",
+            source_label="topic-seed",
+        )
+        store.add_entry_topic(
+            "other2023",
+            topic_slug="chemistry",
+            topic_name="Chemistry",
+            source_type="talkorigins",
+            source_url="https://example.org/topics/chemistry",
+            source_label="topic-seed",
+        )
+        store.connection.commit()
+
+        results = store.search_text("graph", topic_slug="biology")
+
+        assert [row["citation_key"] for row in results] == ["seed2024"]
+    finally:
+        store.close()

tests/test_topic_expand.py

@@ -0,0 +1,242 @@
+from citegeist.bibtex import BibEntry
+from citegeist.expand import (
+    ExpansionResult,
+    TopicExpander,
+    _meets_topic_assignment_threshold,
+    _topic_relevance_score,
+)
+from citegeist.storage import BibliographyStore
+
+
+class FakeOpenAlexExpander:
+    def __init__(self, results: list[ExpansionResult] | dict[str, list[ExpansionResult]]) -> None:
+        self.results = results
+
+    def expand_entry(self, store, citation_key, relation_type="cites", limit=25):
+        if isinstance(self.results, dict):
+            return list(self.results.get(citation_key, []))
+        return list(self.results)
+
+
+def test_topic_expander_assigns_relevant_discoveries_back_to_topic():
+    store = BibliographyStore()
+    try:
+        store.ingest_bibtex(
+            """
+@article{seed2024,
+  author = {Seed, Alice},
+  title = {Abiogenesis Seed Paper},
+  year = {2024}
+}
+"""
+        )
+        store.add_entry_topic(
+            "seed2024",
+            topic_slug="abiogenesis",
+            topic_name="Abiogenesis",
+            source_type="talkorigins",
+            source_url="https://example.org/topics/abiogenesis",
+            source_label="seed",
+        )
+        store.upsert_entry(
+            BibEntry(
+                entry_type="article",
+                citation_key="discovered1",
+                fields={
+                    "title": "Abiogenesis and origin chemistry",
+                    "abstract": "A study of abiogenesis pathways.",
+                    "year": "2025",
+                },
+            ),
+            source_type="graph_expand",
+            source_label="test",
+            review_status="draft",
+        )
+        store.upsert_entry(
+            BibEntry(
+                entry_type="article",
+                citation_key="discovered2",
+                fields={
+                    "title": "Galaxy formation dynamics",
+                    "abstract": "Nothing about the topic.",
+                    "year": "2025",
+                },
+            ),
+            source_type="graph_expand",
+            source_label="test",
+            review_status="draft",
+        )
+        store.connection.commit()
+
+        expander = TopicExpander(
+            openalex_expander=FakeOpenAlexExpander(
+                [
+                    ExpansionResult("seed2024", "discovered1", False, "cites", "openalex:cites:seed2024"),
+                    ExpansionResult("seed2024", "discovered2", False, "cites", "openalex:cites:seed2024"),
+                ]
+            )
+        )
+
+        results = expander.expand_topic(
+            store,
+            "abiogenesis",
+            topic_phrase="abiogenesis origin chemistry",
+            min_relevance=0.34,
+        )
+
+        assert len(results) == 2
+        assigned = {item.discovered_citation_key: item.assigned_to_topic for item in results}
+        assert assigned["discovered1"] is True
+        assert assigned["discovered2"] is False
+        topics = store.get_entry_topics("discovered1")
+        assert topics[0]["slug"] == "abiogenesis"
+        assert store.get_entry_topics("discovered2") == []
+    finally:
+        store.close()
+
+
+def test_topic_expander_can_restrict_to_allowed_seed_keys():
+    store = BibliographyStore()
+    try:
+        store.ingest_bibtex(
+            """
+@article{seed2024,
+  author = {Seed, Alice},
+  title = {Abiogenesis Seed Paper},
+  year = {2024}
+}
+
+@article{seed2023,
+  author = {Seed, Bob},
+  title = {Abiogenesis Historical Seed},
+  year = {2023}
+}
+"""
+        )
+        for citation_key in ("seed2024", "seed2023"):
+            store.add_entry_topic(
+                citation_key,
+                topic_slug="abiogenesis",
+                topic_name="Abiogenesis",
+                source_type="talkorigins",
+                source_url="https://example.org/topics/abiogenesis",
+                source_label="seed",
+            )
+        store.upsert_entry(
+            BibEntry(
+                entry_type="article",
+                citation_key="discovered1",
+                fields={
+                    "title": "Abiogenesis origin chemistry",
+                    "abstract": "A study of abiogenesis chemistry.",
+                    "year": "2025",
+                },
+            ),
+            source_type="graph_expand",
+            source_label="test",
+            review_status="draft",
+        )
+        store.connection.commit()
+
+        expander = TopicExpander(
+            openalex_expander=FakeOpenAlexExpander(
+                {"seed2023": [ExpansionResult("seed2023", "discovered1", False, "cites", "openalex:cites:seed2023")]}
+            )
+        )
+
+        results = expander.expand_topic(
+            store,
+            "abiogenesis",
+            topic_phrase="abiogenesis origin chemistry",
+            seed_keys=["seed2024"],
+        )
+
+        assert results == []
+        assert store.get_entry_topics("discovered1") == []
+    finally:
+        store.close()
+
+
+def test_topic_expander_preview_discovers_without_writing():
+    store = BibliographyStore()
+    try:
+        store.ingest_bibtex(
+            """
+@article{seed2024,
+  author = {Seed, Alice},
+  title = {Abiogenesis Seed Paper},
+  year = {2024}
+}
+"""
+        )
+        store.add_entry_topic(
+            "seed2024",
+            topic_slug="abiogenesis",
+            topic_name="Abiogenesis",
+            source_type="talkorigins",
+            source_url="https://example.org/topics/abiogenesis",
+            source_label="seed",
+        )
+        store.connection.commit()
+
+        expander = TopicExpander()
+        expander._preview_discoveries = lambda *_args, **_kwargs: [  # type: ignore[method-assign]
+            (
+                ExpansionResult(
+                    "seed2024",
+                    "preview1",
+                    True,
+                    "cites",
+                    "openalex:cites:seed2024",
+                ),
+                {
+                    "title": "Abiogenesis origin chemistry",
+                    "abstract": "A study of abiogenesis chemistry.",
+                    "year": "2025",
+                },
+            )
+        ]
+
+        results = expander.expand_topic(
+            store,
+            "abiogenesis",
+            topic_phrase="abiogenesis origin chemistry",
+            min_relevance=0.3,
+            preview_only=True,
+        )
+
+        assert len(results) == 1
+        assert results[0].discovered_citation_key == "preview1"
+        assert results[0].meets_relevance_threshold is True
+        assert results[0].assigned_to_topic is False
+        assert results[0].created_entry is True
+        assert store.get_entry("preview1") is None
+        assert store.get_entry_topics("preview1") == []
+    finally:
+        store.close()
+
+
+def test_topic_relevance_score_expands_human_evolution_terms():
+    score = _topic_relevance_score(
+        "human evolution",
+        {
+            "title": "Body size and proportions in early hominids",
+            "abstract": "A fossil and paleolithic perspective on primate ancestry.",
+            "journal": "Science",
+        },
+    )
+
+    assert score >= 0.15
+
+
+def test_topic_assignment_requires_title_anchor():
+    entry = {
+        "title": "Phylogenies and the Comparative Method",
+        "abstract": "A comparative framework for primate and hominid evolution.",
+        "journal": "Systematic Zoology",
+    }
+
+    score = _topic_relevance_score("human evolution", entry)
+
+    assert score >= 0.15
+    assert _meets_topic_assignment_threshold("human evolution", entry, min_relevance=0.15, relevance_score=score) is False