Evidence claim

scVI + scANVI: description

Probabilistic single-cell comparator in the scaLR study: variational autoencoders infer low-dimensional cell representations and the scANVI stage uses annotation labels for cell-type prediction.

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	scverse/scvi-tools README.md Original source ↗ Reviewed profile (2026-09-16): summary at Methods/scaLR performance comparison with different pipelines (paragraph 6); Results/Comparison of scaLR extracted top 3,500 features as input for different pipelines (paragraph 1); architecture fact at Methods/scaLR performance comparison with different pipelines (paragraph 6); Methods/scaLR performance comparison with different pipelines (paragraph 3); description text also read at Methods/scaLR performance comparison with different pipelines (scVI-tools description) Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 73b28e44223621470e582a81a102c107bb22678b Retrieved: 2026-09-16T20:00:02.370441+00:00	not individually reviewed No individual claim review recorded Audit details Field: `attributes.field` Source artifact SHA-256: `eb46b8a54e60643ca0cd8cb375ede05b01dcbd2380ca17ce8027a92ba13cebbb` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Claimed field description Context-only references	scaLR: a low-resource deep neural network-based platform for single cell analysis and biomarker discovery Original source ↗ Reviewed profile (2026-09-16): summary at Methods/scaLR performance comparison with different pipelines (paragraph 6); Results/Comparison of scaLR extracted top 3,500 features as input for different pipelines (paragraph 1); architecture fact at Methods/scaLR performance comparison with different pipelines (paragraph 6); Methods/scaLR performance comparison with different pipelines (paragraph 3); description text also read at Methods/scaLR performance comparison with different pipelines (scVI-tools description) Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: version of record Retrieved: 2026-09-16T10:44:03.403844+00:00	not individually reviewed No individual claim review recorded Audit details Field: `attributes.field` Source artifact SHA-256: `829afab6a4e30997c608745d3eb280105b8c5c4e601020ffdc55c866144527ca` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Previous value Identity as reported in this paper. Unspecified versions are not assumed equivalent to other papers. Context-only references	scverse/scvi-tools README.md Original source ↗ Reviewed profile (2026-09-16): summary at Methods/scaLR performance comparison with different pipelines (paragraph 6); Results/Comparison of scaLR extracted top 3,500 features as input for different pipelines (paragraph 1); architecture fact at Methods/scaLR performance comparison with different pipelines (paragraph 6); Methods/scaLR performance comparison with different pipelines (paragraph 3); description text also read at Methods/scaLR performance comparison with different pipelines (scVI-tools description) Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 73b28e44223621470e582a81a102c107bb22678b Retrieved: 2026-09-16T20:00:02.370441+00:00	not individually reviewed No individual claim review recorded Audit details Field: `attributes.previous_value` Source artifact SHA-256: `eb46b8a54e60643ca0cd8cb375ede05b01dcbd2380ca17ce8027a92ba13cebbb` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Previous value Identity as reported in this paper. Unspecified versions are not assumed equivalent to other papers. Context-only references	scaLR: a low-resource deep neural network-based platform for single cell analysis and biomarker discovery Original source ↗ Reviewed profile (2026-09-16): summary at Methods/scaLR performance comparison with different pipelines (paragraph 6); Results/Comparison of scaLR extracted top 3,500 features as input for different pipelines (paragraph 1); architecture fact at Methods/scaLR performance comparison with different pipelines (paragraph 6); Methods/scaLR performance comparison with different pipelines (paragraph 3); description text also read at Methods/scaLR performance comparison with different pipelines (scVI-tools description) Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: version of record Retrieved: 2026-09-16T10:44:03.403844+00:00	not individually reviewed No individual claim review recorded Audit details Field: `attributes.previous_value` Source artifact SHA-256: `829afab6a4e30997c608745d3eb280105b8c5c4e601020ffdc55c866144527ca` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Source location Reviewed profile (2026-09-16): summary at Methods/scaLR performance comparison with different pipelines (paragraph 6); Results/Comparison of scaLR extracted top 3,500 features as input for different pipelines (paragraph 1); architecture fact at Methods/scaLR performance comparison with different pipelines (paragraph 6); Methods/scaLR performance comparison with different pipelines (paragraph 3); description text also read at Methods/scaLR performance comparison with different pipelines (scVI-tools description) Context-only references	scverse/scvi-tools README.md Original source ↗ Reviewed profile (2026-09-16): summary at Methods/scaLR performance comparison with different pipelines (paragraph 6); Results/Comparison of scaLR extracted top 3,500 features as input for different pipelines (paragraph 1); architecture fact at Methods/scaLR performance comparison with different pipelines (paragraph 6); Methods/scaLR performance comparison with different pipelines (paragraph 3); description text also read at Methods/scaLR performance comparison with different pipelines (scVI-tools description) Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 73b28e44223621470e582a81a102c107bb22678b Retrieved: 2026-09-16T20:00:02.370441+00:00	not individually reviewed No individual claim review recorded Audit details Field: `attributes.source_locator` Source artifact SHA-256: `eb46b8a54e60643ca0cd8cb375ede05b01dcbd2380ca17ce8027a92ba13cebbb` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Source location Reviewed profile (2026-09-16): summary at Methods/scaLR performance comparison with different pipelines (paragraph 6); Results/Comparison of scaLR extracted top 3,500 features as input for different pipelines (paragraph 1); architecture fact at Methods/scaLR performance comparison with different pipelines (paragraph 6); Methods/scaLR performance comparison with different pipelines (paragraph 3); description text also read at Methods/scaLR performance comparison with different pipelines (scVI-tools description) Context-only references	scaLR: a low-resource deep neural network-based platform for single cell analysis and biomarker discovery Original source ↗ Reviewed profile (2026-09-16): summary at Methods/scaLR performance comparison with different pipelines (paragraph 6); Results/Comparison of scaLR extracted top 3,500 features as input for different pipelines (paragraph 1); architecture fact at Methods/scaLR performance comparison with different pipelines (paragraph 6); Methods/scaLR performance comparison with different pipelines (paragraph 3); description text also read at Methods/scaLR performance comparison with different pipelines (scVI-tools description) Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: version of record Retrieved: 2026-09-16T10:44:03.403844+00:00	not individually reviewed No individual claim review recorded Audit details Field: `attributes.source_locator` Source artifact SHA-256: `829afab6a4e30997c608745d3eb280105b8c5c4e601020ffdc55c866144527ca` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Claimed value Probabilistic single-cell comparator in the scaLR study: variational autoencoders infer low-dimensional cell representations and the scANVI stage uses annotation labels for cell-type prediction. Context-only references	scverse/scvi-tools README.md Original source ↗ Reviewed profile (2026-09-16): summary at Methods/scaLR performance comparison with different pipelines (paragraph 6); Results/Comparison of scaLR extracted top 3,500 features as input for different pipelines (paragraph 1); architecture fact at Methods/scaLR performance comparison with different pipelines (paragraph 6); Methods/scaLR performance comparison with different pipelines (paragraph 3); description text also read at Methods/scaLR performance comparison with different pipelines (scVI-tools description) Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 73b28e44223621470e582a81a102c107bb22678b Retrieved: 2026-09-16T20:00:02.370441+00:00	not individually reviewed No individual claim review recorded Audit details Field: `attributes.value` Source artifact SHA-256: `eb46b8a54e60643ca0cd8cb375ede05b01dcbd2380ca17ce8027a92ba13cebbb` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Claimed value Probabilistic single-cell comparator in the scaLR study: variational autoencoders infer low-dimensional cell representations and the scANVI stage uses annotation labels for cell-type prediction. Context-only references	scaLR: a low-resource deep neural network-based platform for single cell analysis and biomarker discovery Original source ↗ Reviewed profile (2026-09-16): summary at Methods/scaLR performance comparison with different pipelines (paragraph 6); Results/Comparison of scaLR extracted top 3,500 features as input for different pipelines (paragraph 1); architecture fact at Methods/scaLR performance comparison with different pipelines (paragraph 6); Methods/scaLR performance comparison with different pipelines (paragraph 3); description text also read at Methods/scaLR performance comparison with different pipelines (scVI-tools description) Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: version of record Retrieved: 2026-09-16T10:44:03.403844+00:00	not individually reviewed No individual claim review recorded Audit details Field: `attributes.value` Source artifact SHA-256: `829afab6a4e30997c608745d3eb280105b8c5c4e601020ffdc55c866144527ca` 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	scverse/scvi-tools README.md Original source ↗ Reviewed profile (2026-09-16): summary at Methods/scaLR performance comparison with different pipelines (paragraph 6); Results/Comparison of scaLR extracted top 3,500 features as input for different pipelines (paragraph 1); architecture fact at Methods/scaLR performance comparison with different pipelines (paragraph 6); Methods/scaLR performance comparison with different pipelines (paragraph 3); description text also read at Methods/scaLR performance comparison with different pipelines (scVI-tools description) Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 73b28e44223621470e582a81a102c107bb22678b Retrieved: 2026-09-16T20:00:02.370441+00:00	not individually reviewed No individual claim review recorded Audit details Field: `description` Source artifact SHA-256: `eb46b8a54e60643ca0cd8cb375ede05b01dcbd2380ca17ce8027a92ba13cebbb` 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	scaLR: a low-resource deep neural network-based platform for single cell analysis and biomarker discovery Original source ↗ Reviewed profile (2026-09-16): summary at Methods/scaLR performance comparison with different pipelines (paragraph 6); Results/Comparison of scaLR extracted top 3,500 features as input for different pipelines (paragraph 1); architecture fact at Methods/scaLR performance comparison with different pipelines (paragraph 6); Methods/scaLR performance comparison with different pipelines (paragraph 3); description text also read at Methods/scaLR performance comparison with different pipelines (scVI-tools description) Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: version of record Retrieved: 2026-09-16T10:44:03.403844+00:00	not individually reviewed No individual claim review recorded Audit details Field: `description` Source artifact SHA-256: `829afab6a4e30997c608745d3eb280105b8c5c4e601020ffdc55c866144527ca` 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

scaLR: a low-resource deep neural network-based platform for single cell analysis and biomarker discovery · Original source · version of record
scverse/scvi-tools README.md · Original source · 73b28e44223621470e582a81a102c107bb22678b

Download this release (gzip)

Technical metadata and extraction receipts

Stable ID: metadata-correction-afa895e6e86a393a4609

areas: cells-tissues
field: description
previous value: Identity as reported in this paper. Unspecified versions are not assumed equivalent to other papers.
value: Probabilistic single-cell comparator in the scaLR study: variational autoencoders infer low-dimensional cell representations and the scANVI stage uses annotation labels for cell-type prediction.
source locator: Reviewed profile (2026-09-16): summary at Methods/scaLR performance comparison with different pipelines (paragraph 6); Results/Comparison of scaLR extracted top 3,500 features as input for different pipelines (paragraph 1); architecture fact at Methods/scaLR performance comparison with different pipelines (paragraph 6); Methods/scaLR performance comparison with different pipelines (paragraph 3); description text also read at Methods/scaLR performance comparison with different pipelines (scVI-tools description)
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 all 11 scTab and MPRabc method descriptions against PMC11298532 and PMC13232518, and Lazypipe-nt, scaLR, CATHe2, DiffDock-NMDN, PC-mer and Hi-Enhancer against their papers; all match. The other pipeline descriptions are consistent with their pinned papers.; receipt: data/omics/qa-descriptions-20261011-c/review.json

Related records

subject: scVI + scANVI

Suggest a correction