query_format: egfrnsclc-20261009-protocol-lin2025-oncokb-level-assignment
Descriptive fact transcribed from the pinned source.
Evidence
Source checking verifies the cited claim or transcription. It does not establish independent reproduction.
Evidence table
Inspect claims, sources and review details
Trace each statement to its source and review. A context-only reference supports the record generally; it does not verify an individual field. Source checking does not reproduce an experiment.
One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.
6 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| attributes.field query_format Context-only references | Benchmarking large language models GPT-4o, llama 3.1, and qwen 2.5 for cancer genetic variant classification Methods 'Testing framework design' (P44-P45) Version: npj Precision Oncology 9:141, published 2025-05-15; PMC12078457 full-text XML | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| attributes.source_locator Methods 'Testing framework design' (P44-P45) Context-only references | Benchmarking large language models GPT-4o, llama 3.1, and qwen 2.5 for cancer genetic variant classification Methods 'Testing framework design' (P44-P45) Version: npj Precision Oncology 9:141, published 2025-05-15; PMC12078457 full-text XML | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| attributes.value Queries were generated from gene, alteration and tumour type, for example: 'Given the gene EGFR, with alteration L858R in the context of non-small cell lung cancer, what is the appropriate classification?' Context-only references | Benchmarking large language models GPT-4o, llama 3.1, and qwen 2.5 for cancer genetic variant classification Methods 'Testing framework design' (P44-P45) Version: npj Precision Oncology 9:141, published 2025-05-15; PMC12078457 full-text XML | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| description Descriptive fact transcribed from the pinned source. Context-only references | Benchmarking large language models GPT-4o, llama 3.1, and qwen 2.5 for cancer genetic variant classification Methods 'Testing framework design' (P44-P45) Version: npj Precision Oncology 9:141, published 2025-05-15; PMC12078457 full-text XML | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Relationship: subject egfrnsclc-20261009-protocol-lin2025-oncokb-level-assignment Context-only references | Benchmarking large language models GPT-4o, llama 3.1, and qwen 2.5 for cancer genetic variant classification Methods 'Testing framework design' (P44-P45) Version: npj Precision Oncology 9:141, published 2025-05-15; PMC12078457 full-text XML | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| name query_format: egfrnsclc-20261009-protocol-lin2025-oncokb-level-assignment Context-only references | Benchmarking large language models GPT-4o, llama 3.1, and qwen 2.5 for cancer genetic variant classification Methods 'Testing framework design' (P44-P45) Version: npj Precision Oncology 9:141, published 2025-05-15; PMC12078457 full-text XML | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Sources and history
Release 2026-10-10-7b8f80935f90 · Record review: source checked
1 source records and release history
- Benchmarking large language models GPT-4o, llama 3.1, and qwen 2.5 for cancer genetic variant classification · Original source · npj Precision Oncology 9:141, published 2025-05-15; PMC12078457 full-text XML
Technical metadata and extraction receipts
Stable ID: egfrnsclc-20261009-claim-lin2025-query-example
- field
- query_format
- value
- Queries were generated from gene, alteration and tumour type, for example: 'Given the gene EGFR, with alteration L858R in the context of non-small cell lung cancer, what is the appropriate classification?'
- source locator
- Methods 'Testing framework design' (P44-P45)
- review
- method: source-hash-verification; ai-assisted-source-review; method note: Re-downloaded the cited artifacts, matched their SHA-256 and compared the claim with the cited paragraph or table rows.; reviewer: claude; reviewer note: Separate Claude review agent, independent of the extractor; no human review claimed; date: 2026-10-09; artifact sha256: 09c67fcaf7b367d74500db5fd015968389371dcb9ee5a37ccc83241aa63c0f80; retrieval url: https://www.ebi.ac.uk/europepmc/webservices/rest/PMC12078457/fullTextXML; note: Text matches the source. Descriptive claim; no value or execution.