Evidence claim

Relevance of Splice-altering variant classification, CI-SpliceAI benchmark variant set (1,316 variants) (Fortier et al. Table 1) to "Select a patient-RNA splicing-variant validation workflow"

Use case: Select a patient-RNA splicing-variant validation workflow
Assessed by: Splice-altering variant classification, CI-SpliceAI benchmark variant set (1,316 variants) (Fortier et al. Table 1)
Relevance: Proxy evidence
Endpoint: Sensitivity, specificity, F1 and balanced accuracy of SpliceAI, CI-SpliceAI, OpenSpliceAI and a legacy N-of-4 vote on the CI-SpliceAI benchmark variant set (1,316 variants)

Proxy: DNA-based splice predictors scored against experimentally established splicing outcomes, the sequence-classification kind of evidence the use case keeps separate from patient-RNA recovery; inputs are variants, not patient RNA-seq.

4 reviewed evaluations

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.

19 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-10-22-1b7cf027e4f6
Property and statement	Original source and location	Review and provenance
Citation locations 1 values source id rna-splicing-20261011-fortier2026-source-article locator Methods 'CI-SpliceAI benchmark dataset'; Table 1 Context-only references	Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) Original source ↗ rna-splicing-20261011-fortier2026-source-article: Methods 'CI-SpliceAI benchmark dataset'; Table 1 Version: PLOS One 21(5):e0348885, published 2026-05-13; PMC13170886 full-text XML Retrieved: 2026-10-11T21:37:04Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.citation_locators` Source artifact SHA-256: `dffe74cee7782cbdfdbc9423cf00f0a846b3d720b90b10e9732d6f768c485176` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison group fortier2026-spliceai-reimplementations Context-only references	Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) Original source ↗ rna-splicing-20261011-fortier2026-source-article: Methods 'CI-SpliceAI benchmark dataset'; Table 1 Version: PLOS One 21(5):e0348885, published 2026-05-13; PMC13170886 full-text XML Retrieved: 2026-10-11T21:37:04Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.comparison_group` Source artifact SHA-256: `dffe74cee7782cbdfdbc9423cf00f0a846b3d720b90b10e9732d6f768c485176` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison title SpliceAI and its open-source reimplementations on six splice benchmarks (Fortier et al. 2026) Context-only references	Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) Original source ↗ rna-splicing-20261011-fortier2026-source-article: Methods 'CI-SpliceAI benchmark dataset'; Table 1 Version: PLOS One 21(5):e0348885, published 2026-05-13; PMC13170886 full-text XML Retrieved: 2026-10-11T21:37:04Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.comparison_title` Source artifact SHA-256: `dffe74cee7782cbdfdbc9423cf00f0a846b3d720b90b10e9732d6f768c485176` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Constraints 2 values Inspect every linked evaluation's source locator before citing a result. Do not combine this mapping's evaluations with any other protocol's results; variant sets, labels and thresholds differ. Context-only references	Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) Original source ↗ rna-splicing-20261011-fortier2026-source-article: Methods 'CI-SpliceAI benchmark dataset'; Table 1 Version: PLOS One 21(5):e0348885, published 2026-05-13; PMC13170886 full-text XML Retrieved: 2026-10-11T21:37:04Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.constraints` Source artifact SHA-256: `dffe74cee7782cbdfdbc9423cf00f0a846b3d720b90b10e9732d6f768c485176` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Endpoint Sensitivity, specificity, F1 and balanced accuracy of SpliceAI, CI-SpliceAI, OpenSpliceAI and a legacy N-of-4 vote on the CI-SpliceAI benchmark variant set (1,316 variants) Context-only references	Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) Original source ↗ rna-splicing-20261011-fortier2026-source-article: Methods 'CI-SpliceAI benchmark dataset'; Table 1 Version: PLOS One 21(5):e0348885, published 2026-05-13; PMC13170886 full-text XML Retrieved: 2026-10-11T21:37:04Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.endpoint` Source artifact SHA-256: `dffe74cee7782cbdfdbc9423cf00f0a846b3d720b90b10e9732d6f768c485176` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Claimed field links:assessed_by:rna-splicing-20261011-fortier2026-protocol-ci-spliceai-benchmark Context-only references	Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) Original source ↗ rna-splicing-20261011-fortier2026-source-article: Methods 'CI-SpliceAI benchmark dataset'; Table 1 Version: PLOS One 21(5):e0348885, published 2026-05-13; PMC13170886 full-text XML Retrieved: 2026-10-11T21:37:04Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.field` Source artifact SHA-256: `dffe74cee7782cbdfdbc9423cf00f0a846b3d720b90b10e9732d6f768c485176` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Headline metric balanced-accuracy Context-only references	Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) Original source ↗ rna-splicing-20261011-fortier2026-source-article: Methods 'CI-SpliceAI benchmark dataset'; Table 1 Version: PLOS One 21(5):e0348885, published 2026-05-13; PMC13170886 full-text XML Retrieved: 2026-10-11T21:37:04Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.headline_metric` Source artifact SHA-256: `dffe74cee7782cbdfdbc9423cf00f0a846b3d720b90b10e9732d6f768c485176` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Limitations 5 values Labels and variant sets are reused from earlier publications. CI-SpliceAI was trained on all human chromosomes, so no benchmark variant is held out from its training; ABCA4 lies on a test chromosome held out by both SpliceAI and OpenSpliceAI (Methods 'Technical overview of deep learning methods'; Discussion). No uncertainty intervals are printed; significance is from two-proportion Z-tests on accuracy in the Results. Independent of the SpliceAI, CI-SpliceAI and OpenSpliceAI developers; the authors' employer supplies the Legacy Ensemble software, so those rows are author_reported. Variant-level splicing effect, not pathogenicity or diagnostic yield; tissue context is not modelled. The variant set was assembled and published by the CI-SpliceAI developers (reference 9). Context-only references	Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) Original source ↗ rna-splicing-20261011-fortier2026-source-article: Methods 'CI-SpliceAI benchmark dataset'; Table 1 Version: PLOS One 21(5):e0348885, published 2026-05-13; PMC13170886 full-text XML Retrieved: 2026-10-11T21:37:04Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.limitations` Source artifact SHA-256: `dffe74cee7782cbdfdbc9423cf00f0a846b3d720b90b10e9732d6f768c485176` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
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attributes.printed_value attributes.numeric_value sha256 0f055e6fc736d3fc86640720cef7da12a4af7d9e9e8dcd354e84802167f744c0 record id rna-splicing-20261011-fortier2026-result-ci-spliceai-benchmark-spliceai-recall fields status attributes.metric attributes.metric_qualifier attributes.printed_value attributes.numeric_value sha256 ebcbe0e4651d31b497d9fd632e41b577fc12a029642bc47a84c2055ab548b8ea record id rna-splicing-20261011-fortier2026-result-ci-spliceai-benchmark-spliceai-specificity fields status attributes.metric attributes.metric_qualifier attributes.printed_value attributes.numeric_value sha256 383b08f1fd79e02c6ca0d9a219d08461b5d6924d845ac9b1c2c67db4eaa9bda0 record id rna-splicing-20261011-fortier2026-source-article fields status attributes.artifact_sha256 sha256 f632aac0a971c54f908ad18bc9965d498c05b69bd07552d9915807db55a22233 record id use-case-patient-rna-splicing-validation fields status name description facets attributes.question attributes.decision attributes.inputs attributes.output attributes.exclusions attributes.setting attributes.clinical_scope attributes.intended_users sha256 b85cad56e15fbfad66a2e70c3b193ed56c464e5e44b62a19b12f391e409ec897 Context-only references	Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) Original source ↗ rna-splicing-20261011-fortier2026-source-article: Methods 'CI-SpliceAI benchmark dataset'; Table 1 Version: PLOS One 21(5):e0348885, published 2026-05-13; PMC13170886 full-text XML Retrieved: 2026-10-11T21:37:04Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.pins` Source artifact SHA-256: `dffe74cee7782cbdfdbc9423cf00f0a846b3d720b90b10e9732d6f768c485176` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Rationale Proxy: DNA-based splice predictors scored against experimentally established splicing outcomes, the sequence-classification kind of evidence the use case keeps separate from patient-RNA recovery; inputs are variants, not patient RNA-seq. Context-only references	Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) Original source ↗ rna-splicing-20261011-fortier2026-source-article: Methods 'CI-SpliceAI benchmark dataset'; Table 1 Version: PLOS One 21(5):e0348885, published 2026-05-13; PMC13170886 full-text XML Retrieved: 2026-10-11T21:37:04Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.rationale` Source artifact SHA-256: `dffe74cee7782cbdfdbc9423cf00f0a846b3d720b90b10e9732d6f768c485176` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact

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Release 2026-10-22-1b7cf027e4f6 · Record review: source checked

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Analyzing the performance of deep learning splice prediction algorithms (Fortier, Rudy and Scherer, PLOS One 2026) · Original source · PLOS One 21(5):e0348885, published 2026-05-13; PMC13170886 full-text XML

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Technical metadata and extraction receipts

Stable ID: use-case-mapping-rna-splicing-20261011-fortier2026-ci-spliceai-benchmark

field: links:assessed_by:rna-splicing-20261011-fortier2026-protocol-ci-spliceai-benchmark
value: rna-splicing-20261011-fortier2026-protocol-ci-spliceai-benchmark
relevance: proxy
endpoint: Sensitivity, specificity, F1 and balanced accuracy of SpliceAI, CI-SpliceAI, OpenSpliceAI and a legacy N-of-4 vote on the CI-SpliceAI benchmark variant set (1,316 variants)
rationale: Proxy: DNA-based splice predictors scored against experimentally established splicing outcomes, the sequence-classification kind of evidence the use case keeps separate from patient-RNA recovery; inputs are variants, not patient RNA-seq.
constraints: Inspect every linked evaluation's source locator before citing a result.; Do not combine this mapping's evaluations with any other protocol's results; variant sets, labels and thresholds differ.
limitations: Labels and variant sets are reused from earlier publications. CI-SpliceAI was trained on all human chromosomes, so no benchmark variant is held out from its training; ABCA4 lies on a test chromosome held out by both SpliceAI and OpenSpliceAI (Methods 'Technical overview of deep learning methods'; Discussion).; No uncertainty intervals are printed; significance is from two-proportion Z-tests on accuracy in the Results.; Independent of the SpliceAI, CI-SpliceAI and OpenSpliceAI developers; the authors' employer supplies the Legacy Ensemble software, so those rows are author_reported.; Variant-level splicing effect, not pathogenicity or diagnostic yield; tissue context is not modelled.; The variant set was assembled and published by the CI-SpliceAI developers (reference 9).
citation locators: source id: rna-splicing-20261011-fortier2026-source-article; locator: Methods 'CI-SpliceAI benchmark dataset'; Table 1
source locator: rna-splicing-20261011-fortier2026-source-article: Methods 'CI-SpliceAI benchmark dataset'; Table 1
headline metric: balanced-accuracy
comparison group: fortier2026-spliceai-reimplementations
comparison title: SpliceAI and its open-source reimplementations on six splice benchmarks (Fortier et al. 2026)
stratum label: CI-SpliceAI benchmark variant set (1,316 variants)
stratum order: 1
reason: Recorded from the 2026-10-11 use-case literature pass (data/omics/use-case-coverage-rna-splicing-20261011-fortier2026). Independently reviewed in docs/reviews/use-cases/splicing-cnv-use-cases-2026-10-12.md.
review: method: source-hash-verification; independent-cell-check; automated-source-review; scope-review; reviewer: claude; reviewer note: Independent Claude review agent reviewer-scnv; did not extract this batch; no human review claimed; date: 2026-10-12; artifact sha256: dffe74cee7782cbdfdbc9423cf00f0a846b3d720b90b10e9732d6f768c485176; retrieval url: https://www.ebi.ac.uk/europepmc/webservices/rest/PMC13170886/fullTextXML; method note: Drafted by the collector agent uc-splicing-cnv from the pinned source.; note: Checked by reviewer-scnv against the pinned source; verdict in docs/reviews/use-cases/splicing-cnv-use-cases-2026-10-12.md and in this batch's review.md.
reviewed evaluations: rna-splicing-20261011-fortier2026-eval-ci-spliceai-benchmark-ci-spliceai; rna-splicing-20261011-fortier2026-eval-ci-spliceai-benchmark-legacy-ensemble; rna-splicing-20261011-fortier2026-eval-ci-spliceai-benchmark-openspliceai; rna-splicing-20261011-fortier2026-eval-ci-spliceai-benchmark-spliceai
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subject: Select a patient-RNA splicing-variant validation workflow

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