Recommendation:
Use a hybrid workflow: capture authoritative metadata and a short evidence snippet for every source first, then use Claude for structured extraction, synthesis, and draft generation while preserving source IDs in-line. Keep a single master reference file (BibTeX/CSV/JSON) and a snapshot of each source (PDF or archived URL) so provenance survives rewrites.

Why this works
Claude is strong at long-context analysis and multi-turn edits, so it’s ideal for iteratively refining literature reviews. The key is forcing explicit source anchors and machine-readable outputs so you can trace any sentence back to an original source.

Decision criteria (pick based on your project):
- Verifiability required: If you need exact page/quote-level provenance, invest time in snapshotting PDFs and using explicit quote+page anchors.
- Budget & infra: Small teams can do a manual capture + Claude prompts. Larger teams or automation needs call for a RAG setup (vector DB + fetcher) and developer time.
- Skill level: Non-technical researchers can follow the manual checklist below; technical teams can automate the same steps into pipelines.

Practical checklist (operate every review like this):
1) Source capture: For each paper, save full metadata (title, authors, year, DOI, URL), and snapshot the PDF or archive the URL (Wayback or enterprise storage). Give each source a stable ID: S1, S2, etc.
2) Metadata master file: Store metadata in one file (BibTeX or CSV or JSON). This is your single source of truth.
3) Extraction prompt (use with Claude): Ask Claude to output structured JSON. Example prompt:
- "For source S1 (include URL), extract: title, authors, year, doi, 1-sentence summary, 3 key claims with exact quote + page, and a confidence score. Output only valid JSON."
- Insist on quote + page fields and include the source ID with every claim.
4) Inline anchoring in drafts: When Claude writes sentences, require it to append [S#] for the source and (quote,page) if a direct claim. E.g., "X increases Y [S3] (p.12)".
5) Maintain a provenance column: Keep a running table that maps each paragraph/claim to the source IDs and the Claude prompt used to produce it.
6) Bibliography output: At the final draft, ask Claude to produce a formatted bibliography from your master metadata (APA/MLA/BibTeX), cross-checked against DOIs.
7) Verification pass: Manually (or semi-automatically) check any high-stakes claims by opening the snapshot and validating quote/page/interpretation.
8) Versioning & logs: Save each major draft and the exact prompts/instructions you gave Claude (store these with timestamps). Use Git or cloud folders for auditability.

Best-for / Avoid-if
- Best-for: long reviews with many sources, multi-round refinement, teams that need readable syntheses plus traceable claims. Claude’s long-context handling helps keep anchors in place across drafts.
- Avoid-if: you need legally guaranteed provenance (court-level) without additional human verification; also avoid relying solely on model-generated links—always verify DOIs/URLs.

Quick template to ask Claude for a draft paragraph while preserving provenance:
"Write a 3–4 sentence synthesis of findings about X. For each claim include the source ID(s) in square brackets and, for any direct facts, the quoted phrase with page number in parentheses. Use only sources from this list: [S1,S4,S7]."

If you’d like, I can convert this into a ready-to-use Claude prompt library and a small metadata CSV template.

Compare Claude and ChatGPT