Evidence claim

Frame-aware k-mer random forest: description

Description of Frame-aware k-mer random forest

Random forest whose input is the k-mer counts of the sequence computed separately for each of the three reading frames, trained on the same MPRA training set as FramePool50.

Replace a placeholder description with a sourced functional description (issue #88). Historical releases retain the original value.

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.

14 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-11-02-a7f03c9e55a5
Property and statement	Original source and location	Review and provenance
Claimed field description Context-only references	FramePool 2021 primary article Original source ↗ uc20260930-source-framepool-2021: Methods, Random forest models ('the framed_forest model. This random forest takes as input the k-mer-counts for each frame (giving a vector of length 3*(4^k))'); S7 Fig caption Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 2021 journal article XML; PMC8136849.1 Retrieved: 2026-09-30	not individually reviewed No individual claim review recorded Audit details Field: `attributes.field` Source artifact SHA-256: `689af3ecab7b5a928eacc5a76d965960708cbb253fc7cdeae463b16d30ffd2e3` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Claimed field description Context-only references	FramePool Supplementary Table S4 Original source ↗ uc20260930-source-framepool-2021: Methods, Random forest models ('the framed_forest model. This random forest takes as input the k-mer-counts for each frame (giving a vector of length 3*(4^k))'); S7 Fig caption Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 2021 published S4 XLSX Retrieved: 2026-09-30	not individually reviewed No individual claim review recorded Audit details Field: `attributes.field` Source artifact SHA-256: `38659a19f65ad0b64186d5bed88977c7d730f08ebdd38e323c908bea14cbbd89` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Previous value Named prediction method identified in the cited primary source. Exact fitted configurations and scores are separate records. Context-only references	FramePool 2021 primary article Original source ↗ uc20260930-source-framepool-2021: Methods, Random forest models ('the framed_forest model. This random forest takes as input the k-mer-counts for each frame (giving a vector of length 3*(4^k))'); S7 Fig caption Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 2021 journal article XML; PMC8136849.1 Retrieved: 2026-09-30	not individually reviewed No individual claim review recorded Audit details Field: `attributes.previous_value` Source artifact SHA-256: `689af3ecab7b5a928eacc5a76d965960708cbb253fc7cdeae463b16d30ffd2e3` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Previous value Named prediction method identified in the cited primary source. Exact fitted configurations and scores are separate records. Context-only references	FramePool Supplementary Table S4 Original source ↗ uc20260930-source-framepool-2021: Methods, Random forest models ('the framed_forest model. This random forest takes as input the k-mer-counts for each frame (giving a vector of length 3*(4^k))'); S7 Fig caption Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 2021 published S4 XLSX Retrieved: 2026-09-30	not individually reviewed No individual claim review recorded Audit details Field: `attributes.previous_value` Source artifact SHA-256: `38659a19f65ad0b64186d5bed88977c7d730f08ebdd38e323c908bea14cbbd89` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Source location uc20260930-source-framepool-2021: Methods, Random forest models ('the framed_forest model. This random forest takes as input the k-mer-counts for each frame (giving a vector of length 3*(4^k))'); S7 Fig caption Context-only references	FramePool 2021 primary article Original source ↗ uc20260930-source-framepool-2021: Methods, Random forest models ('the framed_forest model. This random forest takes as input the k-mer-counts for each frame (giving a vector of length 3*(4^k))'); S7 Fig caption Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 2021 journal article XML; PMC8136849.1 Retrieved: 2026-09-30	not individually reviewed No individual claim review recorded Audit details Field: `attributes.source_locator` Source artifact SHA-256: `689af3ecab7b5a928eacc5a76d965960708cbb253fc7cdeae463b16d30ffd2e3` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Source location uc20260930-source-framepool-2021: Methods, Random forest models ('the framed_forest model. This random forest takes as input the k-mer-counts for each frame (giving a vector of length 3*(4^k))'); S7 Fig caption Context-only references	FramePool Supplementary Table S4 Original source ↗ uc20260930-source-framepool-2021: Methods, Random forest models ('the framed_forest model. This random forest takes as input the k-mer-counts for each frame (giving a vector of length 3*(4^k))'); S7 Fig caption Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 2021 published S4 XLSX Retrieved: 2026-09-30	not individually reviewed No individual claim review recorded Audit details Field: `attributes.source_locator` Source artifact SHA-256: `38659a19f65ad0b64186d5bed88977c7d730f08ebdd38e323c908bea14cbbd89` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Claimed value Random forest whose input is the k-mer counts of the sequence computed separately for each of the three reading frames, trained on the same MPRA training set as FramePool50. Context-only references	FramePool 2021 primary article Original source ↗ uc20260930-source-framepool-2021: Methods, Random forest models ('the framed_forest model. This random forest takes as input the k-mer-counts for each frame (giving a vector of length 3*(4^k))'); S7 Fig caption Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 2021 journal article XML; PMC8136849.1 Retrieved: 2026-09-30	not individually reviewed No individual claim review recorded Audit details Field: `attributes.value` Source artifact SHA-256: `689af3ecab7b5a928eacc5a76d965960708cbb253fc7cdeae463b16d30ffd2e3` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Claimed value Random forest whose input is the k-mer counts of the sequence computed separately for each of the three reading frames, trained on the same MPRA training set as FramePool50. Context-only references	FramePool Supplementary Table S4 Original source ↗ uc20260930-source-framepool-2021: Methods, Random forest models ('the framed_forest model. This random forest takes as input the k-mer-counts for each frame (giving a vector of length 3*(4^k))'); S7 Fig caption Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 2021 published S4 XLSX Retrieved: 2026-09-30	not individually reviewed No individual claim review recorded Audit details Field: `attributes.value` Source artifact SHA-256: `38659a19f65ad0b64186d5bed88977c7d730f08ebdd38e323c908bea14cbbd89` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Description Replace a placeholder description with a sourced functional description (issue #88). Historical releases retain the original value. Context-only references	FramePool 2021 primary article Original source ↗ uc20260930-source-framepool-2021: Methods, Random forest models ('the framed_forest model. This random forest takes as input the k-mer-counts for each frame (giving a vector of length 3*(4^k))'); S7 Fig caption Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 2021 journal article XML; PMC8136849.1 Retrieved: 2026-09-30	not individually reviewed No individual claim review recorded Audit details Field: `description` Source artifact SHA-256: `689af3ecab7b5a928eacc5a76d965960708cbb253fc7cdeae463b16d30ffd2e3` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Description Replace a placeholder description with a sourced functional description (issue #88). Historical releases retain the original value. Context-only references	FramePool Supplementary Table S4 Original source ↗ uc20260930-source-framepool-2021: Methods, Random forest models ('the framed_forest model. This random forest takes as input the k-mer-counts for each frame (giving a vector of length 3*(4^k))'); S7 Fig caption Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 2021 published S4 XLSX Retrieved: 2026-09-30	not individually reviewed No individual claim review recorded Audit details Field: `description` Source artifact SHA-256: `38659a19f65ad0b64186d5bed88977c7d730f08ebdd38e323c908bea14cbbd89` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact

How to read the evidence

Sources and history

Release 2026-11-02-a7f03c9e55a5 · Record review: source checked

2 source records and release history

FramePool 2021 primary article · Original source · 2021 journal article XML; PMC8136849.1
FramePool Supplementary Table S4 · Original source · 2021 published S4 XLSX

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Technical metadata and extraction receipts

Stable ID: metadata-correction-28c44174a00c934ba162

areas: rna-transcriptomes
field: description
previous value: Named prediction method identified in the cited primary source. Exact fitted configurations and scores are separate records.
value: Random forest whose input is the k-mer counts of the sequence computed separately for each of the three reading frames, trained on the same MPRA training set as FramePool50.
source locator: uc20260930-source-framepool-2021: Methods, Random forest models ('the framed_forest model. This random forest takes as input the k-mer-counts for each frame (giving a vector of length 3*(4^k))'); S7 Fig caption
review: method: automated-source-review; ai-assisted-source-review; reviewer: claude; reviewer note: Extractor: Claude integrator agent for issue #88. Reviewer: a separate Claude review agent, independent of the extractor; no human review claimed.; date: 2026-10-11; method note: Compared the store diff with origin/main, read each new description against its cited source passage and checked the licence of each new source record.; note: Approved. Checked the 10 method and model descriptions against their sources (EVmutation, GEMME and RSALOR abstracts, the FramePool k-mer random forests, the RhoMax BLASSO text) and spot-checked the 49 mRNABench rows against Appendix A; all accurate. Licences on the 3 new sources match their Europe PMC records. At the reviewer's suggestion, the en dash printed in some checkpoint names is written as a hyphen in the descriptions.; receipt: data/omics/qa-descriptions-20261011-a/review.json

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subject: Frame-aware k-mer random forest

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