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MARGINAL: An Automatic Classification of Variants in BRCA1 and BRCA2 Genes Using a Machine Learning Model

Primary source inspected for author, title and venue only. Headline performance tables were located but no numeric value was transcribed from them this pass; see evidence_concerns.

Evidence

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17 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-10-06-fea06f63ac0e
Property and statement	Original source and location	Review and provenance
attributes.artifact_retrieved_at 2026-10-05T14:01:11Z Source metadata	MARGINAL: An Automatic Classification of Variants in BRCA1 and BRCA2 Genes Using a Machine Learning Model Original source ↗ No field-specific location recorded Version: 2022 published article (Biomolecules) Retrieved: 2026-10-05T14:01:11Z	catalogued No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `attributes.artifact_retrieved_at` Source artifact SHA-256: `9618e7169b71375611f115450d9b17144d8fb67e3241d14dc38c8fa9cebed4ba` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
attributes.artifact_sha256 9618e7169b71375611f115450d9b17144d8fb67e3241d14dc38c8fa9cebed4ba Source metadata	MARGINAL: An Automatic Classification of Variants in BRCA1 and BRCA2 Genes Using a Machine Learning Model Original source ↗ No field-specific location recorded Version: 2022 published article (Biomolecules) Retrieved: 2026-10-05T14:01:11Z	catalogued No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `attributes.artifact_sha256` Source artifact SHA-256: `9618e7169b71375611f115450d9b17144d8fb67e3241d14dc38c8fa9cebed4ba` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
attributes.artifact_url https://pmc.ncbi.nlm.nih.gov/articles/PMC9687470/ Source metadata	MARGINAL: An Automatic Classification of Variants in BRCA1 and BRCA2 Genes Using a Machine Learning Model Original source ↗ No field-specific location recorded Version: 2022 published article (Biomolecules) Retrieved: 2026-10-05T14:01:11Z	catalogued No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `attributes.artifact_url` Source artifact SHA-256: `9618e7169b71375611f115450d9b17144d8fb67e3241d14dc38c8fa9cebed4ba` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
attributes.doi 10.3390/biom12111552 Source metadata	MARGINAL: An Automatic Classification of Variants in BRCA1 and BRCA2 Genes Using a Machine Learning Model Original source ↗ No field-specific location recorded Version: 2022 published article (Biomolecules) Retrieved: 2026-10-05T14:01:11Z	catalogued No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `attributes.doi` Source artifact SHA-256: `9618e7169b71375611f115450d9b17144d8fb67e3241d14dc38c8fa9cebed4ba` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
attributes.evidence_concerns 2 values Headline performance tables are located (Results 3.1, Tables 3-4: held-out 80/20-split classifier comparison on 497 variants; Results 3.3, Table 6: external validation on 11,932 ClinVar variants) but no numeric cell was transcribed from them this pass. This is a value-not-extracted gap, not a resolved or irresolvable source discrepancy. Both the 497-variant held-out labels (CanVaS) and the 11,932-variant external labels (ClinVar) are existing registry classifications, not blinded independent adjudication performed for this study. Source metadata	MARGINAL: An Automatic Classification of Variants in BRCA1 and BRCA2 Genes Using a Machine Learning Model Original source ↗ No field-specific location recorded Version: 2022 published article (Biomolecules) Retrieved: 2026-10-05T14:01:11Z	catalogued No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `attributes.evidence_concerns` Source artifact SHA-256: `9618e7169b71375611f115450d9b17144d8fb67e3241d14dc38c8fa9cebed4ba` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
attributes.publication_status peer_reviewed Source metadata	MARGINAL: An Automatic Classification of Variants in BRCA1 and BRCA2 Genes Using a Machine Learning Model Original source ↗ No field-specific location recorded Version: 2022 published article (Biomolecules) Retrieved: 2026-10-05T14:01:11Z	catalogued No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `attributes.publication_status` Source artifact SHA-256: `9618e7169b71375611f115450d9b17144d8fb67e3241d14dc38c8fa9cebed4ba` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
attributes.retrieved_at 2026-10-05T14:01:11Z Source metadata	MARGINAL: An Automatic Classification of Variants in BRCA1 and BRCA2 Genes Using a Machine Learning Model Original source ↗ No field-specific location recorded Version: 2022 published article (Biomolecules) Retrieved: 2026-10-05T14:01:11Z	catalogued No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `attributes.retrieved_at` Source artifact SHA-256: `9618e7169b71375611f115450d9b17144d8fb67e3241d14dc38c8fa9cebed4ba` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
attributes.url https://pmc.ncbi.nlm.nih.gov/articles/PMC9687470/ Source metadata	MARGINAL: An Automatic Classification of Variants in BRCA1 and BRCA2 Genes Using a Machine Learning Model Original source ↗ No field-specific location recorded Version: 2022 published article (Biomolecules) Retrieved: 2026-10-05T14:01:11Z	catalogued No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `attributes.url` Source artifact SHA-256: `9618e7169b71375611f115450d9b17144d8fb67e3241d14dc38c8fa9cebed4ba` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
attributes.version 2022 published article (Biomolecules) Source metadata	MARGINAL: An Automatic Classification of Variants in BRCA1 and BRCA2 Genes Using a Machine Learning Model Original source ↗ No field-specific location recorded Version: 2022 published article (Biomolecules) Retrieved: 2026-10-05T14:01:11Z	catalogued No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `attributes.version` Source artifact SHA-256: `9618e7169b71375611f115450d9b17144d8fb67e3241d14dc38c8fa9cebed4ba` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
description Primary source inspected for author, title and venue only. Headline performance tables were located but no numeric value was transcribed from them this pass; see evidence_concerns. Source metadata	MARGINAL: An Automatic Classification of Variants in BRCA1 and BRCA2 Genes Using a Machine Learning Model Original source ↗ No field-specific location recorded Version: 2022 published article (Biomolecules) Retrieved: 2026-10-05T14:01:11Z	catalogued No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `description` Source artifact SHA-256: `9618e7169b71375611f115450d9b17144d8fb67e3241d14dc38c8fa9cebed4ba` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact

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Technical metadata and extraction receipts

Stable ID: uc-clinical-20261005-source-marginal

areas: dna-genomes
contexts: clinical_research
url: https://pmc.ncbi.nlm.nih.gov/articles/PMC9687470/
retrieved at: 2026-10-05T14:01:11Z
version: 2022 published article (Biomolecules)
publication status: peer_reviewed
doi: 10.3390/biom12111552
artifact sha256: 9618e7169b71375611f115450d9b17144d8fb67e3241d14dc38c8fa9cebed4ba
artifact url: https://pmc.ncbi.nlm.nih.gov/articles/PMC9687470/
artifact retrieved at: 2026-10-05T14:01:11Z
evidence concerns: Headline performance tables are located (Results 3.1, Tables 3-4: held-out 80/20-split classifier comparison on 497 variants; Results 3.3, Table 6: external validation on 11,932 ClinVar variants) but no numeric cell was transcribed from them this pass. This is a value-not-extracted gap, not a resolved or irresolvable source discrepancy.; Both the 497-variant held-out labels (CanVaS) and the 11,932-variant external labels (ClinVar) are existing registry classifications, not blinded independent adjudication performed for this study.

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