pubmed-verifier（已发布的验证器）

PubMed Citation Verifier v2.1

Five-state batch verification of PMID citations via PubMed E-utilities API, with SQLite caching, CSV support, and Crossref DOI verification.

Verdict Types

Quick Start

# Verify all PMIDs in a project directory (auto-parses citation context)
python3 scripts/verify_pmids.py --source /path/to/project --output report.html

# Verify specific PMIDs
python3 verify_pmids.py --pmids 31018962,22213727

# Verify with explicit claimed metadata (JSON)
python3 verify_pmids.py --claims '[{"pmid":"34078778","title":"JIA pathogenesis","authors":["Zaripova"],"journal":"Pediatr Rheumatol Online J","year":"2021"}]' --output report.html

# Verify with claims file (JSON or CSV)
python3 verify_pmids.py --claims-file claims.csv --suggest --output report.html

# Verify + DOI cross-check via Crossref
python3 verify_pmids.py --source /path/to/files --verify-doi --output report.html

# Full pipeline with all features
python3 verify_pmids.py --source /path/to/files --verify-doi --suggest --output report.html

What's New in v2.1

How It Works

1. Extract PMIDs + Parse Citation Context

Scans files for common PMID patterns (PMID: 12345678, PubMed URLs, etc.).

Automatically parses surrounding citation text to extract claimed metadata:

• Author surnames (e.g., Ravelli A, Martini A → ["Ravelli", "Martini"])
• Paper title (between author and journal)
• Journal name (from <i>...</i> tags or position)
• Publication year (20xx / 19xx)

Supported file types: .html, .md, .txt, .json, .htm

2. Fetch PubMed Metadata (with Cache)

Each PMID queried via PubMed esummary API. Results cached in SQLite for 30 days (configurable via --cache-days). Use --no-cache to force fresh queries.

Batch requests (50/call, 0.4s delay, 3-retry with exponential backoff).

3. Cross-Check: Claimed vs Actual

Dual-strategy fuzzy matching:

• Primary: Word-level Jaccard overlap ≥ 50% (handles word reordering, abbreviation expansion)
• Supplementary: SequenceMatcher ratio ≥ 90% (catches edge cases)

Verdict determination:

• title_match AND (author_match OR journal_match) → ✅ Correct
• author_match AND journal_match AND NOT title_match → 🔶 Partial
• Otherwise → ⚠️ Mismatch

4. Crossref DOI Verification (Optional, --verify-doi)

For articles with DOIs, queries Crossref API to cross-verify title/journal/year as an independent data source.

5. Auto-Suggest (Optional, --suggest)

For mismatches, searches PubMed using claimed metadata to suggest correct PMIDs (top 3 candidates).

6. Topic Relevance (Optional, --match-keywords)

⚠️ Note: This checks *topic relevance* only (via filename keywords), NOT PMID correctness. Auxiliary screening tool.

7. Report Output

Using --claims / --claims-file

When you have explicit claimed metadata (e.g., from AI-generated documents):

JSON array format:

[
  {
    "pmid": "34078778",
    "title": "Juvenile idiopathic arthritis: from pathogenesis to clinical practice",
    "authors": ["Zaripova LN", "Midgley A", "Beresford MW"],
    "journal": "Pediatr Rheumatol Online J",
    "year": "2021"
  }
]

CSV format (claims.csv):

pmid,title,authors,journal,year
34078778,JIA pathogenesis,Zaripova LN;Midgley A,Pediatr Rheumatol Online J,2021
31018962,FMF classification criteria,Lidar M|Lancet,,2014

CLI Reference

python3 scripts/verify_pmids.py [OPTIONS]

Options:
  --source PATH        File or directory to scan for PMIDs
  --pmids P1,P2,...    Comma-separated PMIDs to verify directly
  --claims JSON        JSON string with claimed metadata
  --claims-file FILE   JSON or CSV file with claimed metadata
  --verify-doi         Also verify DOIs via Crossref
  --suggest            Auto-suggest correct PMIDs for mismatches
  --match-keywords     Check topic relevance (auxiliary)
  --threshold FLOAT    Keyword match threshold (default: 0.2)
  --no-cache           Disable cache, always query API
  --cache-days N       Cache validity in days (default: 30)
  --output FILE        Output file (.json or .html)
  --format FORMAT      Output format: json|html|text (default: text)

Fixing Mismatched/Invalid PMIDs

1. Check the report's "Suggested" column (if using --suggest)
2. Use PubMed search to find the correct article:

   from scripts.verify_pmids import search_pubmed
   results = search_pubmed('Ravelli[au] AND juvenile idiopathic arthritis AND Lancet[jour]')
   for r in results: print(r["pmid"], r.get("title",""))

1. Verify the replacement and update the source file

API Limits

• No API key required (public E-utilities)
• 3 requests/second without API key
• Script enforces 0.4s delay between batches, 3-retry with backoff
• Batch size: 50 PMIDs per request
• Cache reduces repeated API calls significantly

Performance

Files