rewire.it
Task

gene-regulatory signal prediction

Gene-regulatory signal prediction tests whether combined representations generalize beyond repeated gene identities.

SourcesResidual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues · Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages

1 evaluation · 1 metric row

At a glance

Inputs, training, access and other details

Explanatory profile: limited source coverage · Automated source review, 2026-09-16. Review applies to the cited claims; unresolved fields are listed below. Numerical results retain their own review status.

Data, procedure and scoring
PropertyDescription and evidence
DatasetsRegulatory-edge evaluation across tissue domains; exact dataset releases remain unextracted.
SourcesResidual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues · Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages
SplitsNested outer-split evaluation is complemented by leave-TF-out, leave-target-out and leave-both-out tests.
SourcesResidual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues · Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages
MetricsAUROC in the reviewed stacked-model comparison.
SourcesResidual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues · Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages
BaselinesCombined representation is compared with the individual model branches.
SourcesResidual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues · Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages
Leakage controlsNested validation separates feature construction from testing; entity-grouped tests address gene-identity carryover.
SourcesResidual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues · Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages
UncertaintyBootstrap confidence intervals support reported comparisons.
SourcesResidual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues · Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages
Entity typePaper-specific computational evaluation protocol.
SourcesResidual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues · Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages
OrganismsHuman tissues from the Tabula Sapiens atlas.
SourcesResidual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues · Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages
AssaysTabula Sapiens single-cell RNA-seq with TRRUST regulatory reference annotations.
SourcesResidual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues · Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages
Allowed inputsCandidate transcription-factor/target pairs and model representations.
SourcesResidual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues · Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages
AdaptationSupervised prediction with nested splits and TF/target holdout stress tests.
SourcesResidual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues · Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages

How it works

How it worksComputational evaluation flow
Computational evaluation flow1. Input: Candidate transcription-factor/target pairs and model representations.. Then: 2. Evaluation: Supervised prediction with nested splits and TF/target holdout stress tests.. Then: 3. Readout: AUROC in the reviewed stacked-model comparison.Computational evaluation flow1. Input: Candidate transcription-factor/target pairs and model representations.. Then: 2. Evaluation: Supervised prediction with nested splits and TF/target holdout stress tests.. Then: 3. Readout: AUROC in the reviewed stacked-model comparison.Computational evaluation flow1. Input: Candidate transcription-factor/target pairs and model representations.. Then: 2. Evaluation: Supervised prediction with nested splits and TF/target holdout stress tests.. Then: 3. Readout: AUROC in the reviewed stacked-model comparison.

Conceptual summary of the cited evaluation; exact task configuration and source version remain part of the protocol.

SourcesResidual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues · Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages
Evaluation methodology

Regulatory-edge evaluation across tissue domains; exact dataset releases remain unextracted. Nested outer-split evaluation is complemented by leave-TF-out, leave-target-out and leave-both-out tests. AUROC in the reviewed stacked-model comparison. Combined representation is compared with the individual model branches. Nested validation separates feature construction from testing; entity-grouped tests address gene-identity carryover. Bootstrap confidence intervals support reported comparisons.

SourcesResidual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues · Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages

Recorded evaluations

Each evaluation records what was tested and under which conditions.

Tested entities and results

Release 2026-09-17-d277315f7d76 · 1 evaluation · 1 metric row. Different protocols are not a single leaderboard.

Results grouped by the exact reported evaluation
Metric and findingCoverage and uncertaintyEvidence
scGPT + residual geometry: gene-regulatory signal prediction

Asymmetric extraction, PCA-64 centered cosine geometry added to scGPT baseline

Author-reported evaluation · Evaluation metadata: needs review

0.677 AUROC

Unit: fraction · Direction: unknown

Uncertainty: not reported in legacy extract

Scored: Not reported · Eligible: Not reported

source checkedResidual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues · Table 4, Immune row, scGPT > +geom AUROC column

Source checking is not independent reproduction.

Papers and result coverage

Last literature check: 2026-09-17. Primary-paper discovery and source inspection. Source-checked results are not independently reproduced experiments.

Paper or primary resourceVersionReference
Residual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissuesversion of recordRead source
DOI: 10.1186/s12859-026-06538-5

What is still missing

  • Original asymmetric extraction in Table 4 is not a fair matched-input comparison; prefer Table 9 with its single-seed context.
  • Strict leave-both-out improvements shrink near zero; do not omit this limitation.
  • Source contains rounded deltas and intervals/significance annotations; do not recompute them from rounded absolute numbers.
Search and extraction details

primary comparison table screened

Searches

  • "PMC13418759"

Evidence locations

  • Tables 7 and 9 and footnotes
  • Results: matched per-layer extraction

Strengths and limitations

Profile review details

Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.

Stable record: reported-task-99afd88cb12895

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.

18 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-09-17-d277315f7d76
Property and statementOriginal source and locationReview and provenance
Diagram caption

Conceptual summary of the cited evaluation; exact task configuration and source version remain part of the protocol.

Individual claims
Residual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues

Original source ↗

Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages

Version: version of record
Retrieved: 2026-09-16T10:41:06Z

source checked

automated source review · 2026-09-16

Audit details

Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.

Field: attributes.profile.diagram.caption

Source artifact SHA-256: 77546faec51cfb5c78b73c5943f940c4e0097d130b1ddde4ab8287b507b36df6

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Diagram steps

["Input: Candidate transcription-factor/target pairs and model representations.","Evaluation: Supervised prediction with nested splits and TF/target holdout stress tests.","Readout: AUROC in the reviewed stacked-model comparison."]

Individual claims
Residual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues

Original source ↗

Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages

Version: version of record
Retrieved: 2026-09-16T10:41:06Z

source checked

automated source review · 2026-09-16

Audit details

Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.

Field: attributes.profile.diagram.steps

Source artifact SHA-256: 77546faec51cfb5c78b73c5943f940c4e0097d130b1ddde4ab8287b507b36df6

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Diagram title

Computational evaluation flow

Individual claims
Residual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues

Original source ↗

Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages

Version: version of record
Retrieved: 2026-09-16T10:41:06Z

source checked

automated source review · 2026-09-16

Audit details

Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.

Field: attributes.profile.diagram.title

Source artifact SHA-256: 77546faec51cfb5c78b73c5943f940c4e0097d130b1ddde4ab8287b507b36df6

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Datasets

Regulatory-edge evaluation across tissue domains; exact dataset releases remain unextracted.

Individual claims
Residual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues

Original source ↗

Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages

Version: version of record
Retrieved: 2026-09-16T10:41:06Z

source checked

automated source review · 2026-09-16

Audit details

Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.

Field: attributes.profile.facts.0.value

Source artifact SHA-256: 77546faec51cfb5c78b73c5943f940c4e0097d130b1ddde4ab8287b507b36df6

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Splits

Nested outer-split evaluation is complemented by leave-TF-out, leave-target-out and leave-both-out tests.

Individual claims
Residual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues

Original source ↗

Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages

Version: version of record
Retrieved: 2026-09-16T10:41:06Z

source checked

automated source review · 2026-09-16

Audit details

Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.

Field: attributes.profile.facts.1.value

Source artifact SHA-256: 77546faec51cfb5c78b73c5943f940c4e0097d130b1ddde4ab8287b507b36df6

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Adaptation

Supervised prediction with nested splits and TF/target holdout stress tests.

Individual claims
Residual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues

Original source ↗

Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages

Version: version of record
Retrieved: 2026-09-16T10:41:06Z

source checked

automated source review · 2026-09-16

Audit details

Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.

Field: attributes.profile.facts.10.value

Source artifact SHA-256: 77546faec51cfb5c78b73c5943f940c4e0097d130b1ddde4ab8287b507b36df6

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Metrics

AUROC in the reviewed stacked-model comparison.

Individual claims
Residual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues

Original source ↗

Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages

Version: version of record
Retrieved: 2026-09-16T10:41:06Z

source checked

automated source review · 2026-09-16

Audit details

Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.

Field: attributes.profile.facts.2.value

Source artifact SHA-256: 77546faec51cfb5c78b73c5943f940c4e0097d130b1ddde4ab8287b507b36df6

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Baselines

Combined representation is compared with the individual model branches.

Individual claims
Residual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues

Original source ↗

Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages

Version: version of record
Retrieved: 2026-09-16T10:41:06Z

source checked

automated source review · 2026-09-16

Audit details

Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.

Field: attributes.profile.facts.3.value

Source artifact SHA-256: 77546faec51cfb5c78b73c5943f940c4e0097d130b1ddde4ab8287b507b36df6

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Leakage controls

Nested validation separates feature construction from testing; entity-grouped tests address gene-identity carryover.

Individual claims
Residual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues

Original source ↗

Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages

Version: version of record
Retrieved: 2026-09-16T10:41:06Z

source checked

automated source review · 2026-09-16

Audit details

Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.

Field: attributes.profile.facts.4.value

Source artifact SHA-256: 77546faec51cfb5c78b73c5943f940c4e0097d130b1ddde4ab8287b507b36df6

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Uncertainty

Bootstrap confidence intervals support reported comparisons.

Individual claims
Residual-stream geometry of single-cell foundation models carries incremental gene-regulatory signal across tissues

Original source ↗

Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages

Version: version of record
Retrieved: 2026-09-16T10:41:06Z

source checked

automated source review · 2026-09-16

Audit details

Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.

Field: attributes.profile.facts.5.value

Source artifact SHA-256: 77546faec51cfb5c78b73c5943f940c4e0097d130b1ddde4ab8287b507b36df6

Hash scope: Hash scope not separately documented; inspect source record

Inspected artifact

Sources and history

Release 2026-09-17-d277315f7d76 · Record review: needs review

2 source records and release historyDownload this release
Technical metadata and extraction receipts

Stable ID: reported-task-99afd88cb12895

areas
cells-tissues
tasks
gene-regulatory signal prediction
entity level
task
version
Not reported
task
gene-regulatory signal prediction
scope note
Paper-specific evaluation task; protocol completeness requires further extraction.
benchmark research
review date: 2026-09-17; status: primary_comparison_table_screened; primary sources: expansion-p3-single-cell-residual-geometry-2026; inspected locators: Tables 7 and 9 and footnotes; Results: matched per-layer extraction; searched queries: "PMC13418759"; gaps: Original asymmetric extraction in Table 4 is not a fair matched-input comparison; prefer Table 9 with its single-seed context.; Strict leave-both-out improvements shrink near zero; do not omit this limitation.; Source contains rounded deltas and intervals/significance annotations; do not recompute them from rounded absolute numbers.; claim scope: Primary-paper discovery and source inspection. Source-checked results are not independently reproduced experiments.
historical missing metadata
protocol version: not_reported_in_legacy_extract; split: not_reported_in_legacy_extract
metadata review scope
historical_missing_metadata preserves the original discovery state. Current descriptive evidence and missingness are recorded in profile.facts; numerical-result review is separate.
legacy kinds
benchmark
entity classification
review date: 2026-09-17; rationale: This source-scoped record identifies the biological prediction task and holds its paper context. Preserve the existing task identity; exact split, model adaptation and scoring remain in linked evaluations or separate protocol records.; source ids: single-cell-residual-geometry-2026; source locator: Results: nested cross-validation; Grouped cross-validation; cached text lines 48–56; Methods dataset and scGPT passages; ambiguities: A paper- or suite-specific task may constrain some inputs or metrics; that alone does not make it interchangeable with a complete versioned protocol. No protocol equivalence is inferred.; Some legacy profile Entity type facts use the generic phrase computational evaluation protocol. That boilerplate is not sufficient to establish a single fixed protocol identity or to merge this task with another protocol record.
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