rewire.it
Task

Human thymus cell-type classification

Human thymus annotation evaluates transfer from a mouse-trained gene representation after homolog mapping.

SourcesMouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility · Results: cross-species human cell classification; cached text line 41

2 evaluations · 2 metric rows

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
DatasetsHuman thymus scRNA-seq data from GSE144870, alongside separate breast and cortex evaluations.
SourcesMouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility · Results: cross-species human cell classification; cached text line 41
SplitsHuman thymus cells come from GSE144870. After mapping human genes to mouse homologues, the fine-tuning experiment randomly uses 80% of cells for training and 20% for testing; the zero-shot column is a separate evaluation setting.
SourcesMouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility · Materials and methods: Human cell type classification using mouse-Geneformer; Table 4
MetricsCell-type classification accuracy.
SourcesMouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility · Results: cross-species human cell classification; cached text line 41
BaselinesMouse-Geneformer and human Geneformer.
SourcesMouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility · Results: cross-species human cell classification; cached text line 41
Leakage controlsThe source states these datasets are outside Genecorpus-30M; this review does not treat its feature-distance check as proof of complete leakage absence.
SourcesMouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility · Results: cross-species human cell classification; cached text line 41
UncertaintyTable 4 prints one accuracy and F1 value per model/setting. Its caption and the human classification method do not report confidence intervals, standard deviations or repeated-split uncertainty for the thymus result. · Not reported in inspected sources
SourcesMouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility · Materials and methods: Human cell type classification using mouse-Geneformer; Table 4 caption
Entity typePaper-specific computational evaluation protocol.
SourcesMouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility · Results: cross-species human cell classification; cached text line 41
OrganismsHuman thymus for the linked test; mouse pretraining is a separate data source.
SourcesMouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility · Results: cross-species human cell classification; cached text line 41
AssaysHuman thymus scRNA-seq cell-type annotations.
SourcesMouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility · Results: cross-species human cell classification; cached text line 41
Allowed inputsGene-expression profiles represented by Geneformer models.
SourcesMouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility · Results: cross-species human cell classification; cached text line 41
AdaptationCross-species representation transfer compared with the human Geneformer baseline.
SourcesMouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility · Results: cross-species human cell classification; cached text line 41

How it works

How it worksComputational evaluation flow
Computational evaluation flow1. Input: Gene-expression profiles represented by Geneformer models.. Then: 2. Evaluation: Human thymus cells come from GSE144870. After mapping human genes to mouse homologues, the fine-tuning experiment randomly uses 80% of cells for training and 20% for testing; the zero-shot column is a separate evaluation setting.. Then: 3. Readout: Cell-type classification accuracy.Computational evaluation flow1. Input: Gene-expression profiles represented by Geneformer models.. Then: 2. Evaluation: Human thymus cells come from GSE144870. After mapping human genes to mouse homologues, the fine-tuning experiment randomly uses 80% of cells for training and 20% for testing; the zero-shot column is a separate evaluation setting.. Then: 3. Readout: Cell-type classification accuracy.Computational evaluation flow1. Input: Gene-expression profiles represented by Geneformer models.. Then: 2. Evaluation: Human thymus cells come from GSE144870. After mapping human genes to mouse homologues, the fine-tuning experiment randomly uses 80% of cells for training and 20% for testing; the zero-shot column is a separate evaluation setting.. Then: 3. Readout: Cell-type classification accuracy.

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

SourcesMouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility · Results: cross-species human cell classification; cached text line 41; Materials and methods: Human cell type classification using mouse-Geneformer; Table 4
Evaluation methodology

Human thymus scRNA-seq data from GSE144870, alongside separate breast and cortex evaluations. Human thymus cells come from GSE144870. After mapping human genes to mouse homologues, the fine-tuning experiment randomly uses 80% of cells for training and 20% for testing; the zero-shot column is a separate evaluation setting. Cell-type classification accuracy. Mouse-Geneformer and human Geneformer. The source states these datasets are outside Genecorpus-30M; this review does not treat its feature-distance check as proof of complete leakage absence.

SourcesMouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility · Results: cross-species human cell classification; cached text line 41; Materials and methods: Human cell type classification using mouse-Geneformer; Table 4

Recorded evaluations

Each evaluation records what was tested and under which conditions.

Tested entities and results

Release 2026-09-17-d277315f7d76 · 2 evaluations · 2 metric rows. Different protocols are not a single leaderboard.

Results grouped by the exact reported evaluation
Metric and findingCoverage and uncertaintyEvidence
Mouse-Geneformer: Human thymus cell-type classification

Ortholog-based gene conversion; zero-shot mouse model on human cells.

Author-reported evaluation · Evaluation metadata: needs review

48.57 F1

Unit: % · Direction: unknown

Uncertainty: not reported in legacy extract

Scored: Not reported · Eligible: Not reported

source checkedMouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility · Table 4, h/ Thymus row, Mouse-Geneformer Zero-shot F1 column

Source checking is not independent reproduction.

Human-Geneformer: Human thymus cell-type classification

Native human model; zero-shot setting.

Independent external evaluation · Evaluation metadata: needs review

74.48 F1

Unit: % · Direction: unknown

Uncertainty: not reported in legacy extract

Scored: Not reported · Eligible: Not reported

source checkedMouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility · Table 4, h/ Thymus row, Human-Geneformer Zero-shot F1 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
Mouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utilityversion of recordRead source
DOI: 10.1371/journal.pgen.1011420

What is still missing

  • Only the thymus row belongs to the assigned benchmark; cortex and breast must be separate protocols.
  • The authors' Euclidean nonidentity check is not proof that all leakage is absent; source wording must not become an independently established guarantee.
  • No replicate uncertainty in Table 4.
Search and extraction details

primary comparison table screened

Searches

  • "mouse" "Geneformer" "PMC11964219"

Evidence locations

  • Table 4 and footnote
  • Methods: Cell type classification
  • Methods: Cross-species application

Strengths and limitations

Strengths and considerations

No source-reviewed explanatory claims are recorded here yet.

Profile review details

Targeted full-paper and supplement review of the outstanding task fields, with original dataset metadata checked where accessible. Source-scoped omissions are explicit; no independent benchmark reproduction or numerical-result change.

Stable record: reported-task-031186b57c62de

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.

17 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
Mouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility

Original source ↗

Results: cross-species human cell classification; cached text line 41; Materials and methods: Human cell type classification using mouse-Geneformer; Table 4

Version: version of record
Retrieved: 2026-09-16T10:44:03.392488+00:00

source checked

automated source review · 2026-09-16

Audit details

Targeted full-paper and supplement review of the outstanding task fields, with original dataset metadata checked where accessible. Source-scoped omissions are explicit; no independent benchmark reproduction or numerical-result change.

Field: attributes.profile.diagram.caption

Source artifact SHA-256: ef6c68f5c9b47c2f89598ddf647f05b72e4155e8b33609ebff23936a84bbd41d

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

Inspected artifact

Diagram steps

["Input: Gene-expression profiles represented by Geneformer models.","Evaluation: Human thymus cells come from GSE144870. After mapping human genes to mouse homologues, the fine-tuning experiment randomly uses 80% of cells for training and 20% for testing; the zero-shot column is a separate evaluation setting.","Readout: Cell-type classification accuracy."]

Individual claims
Mouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility

Original source ↗

Results: cross-species human cell classification; cached text line 41; Materials and methods: Human cell type classification using mouse-Geneformer; Table 4

Version: version of record
Retrieved: 2026-09-16T10:44:03.392488+00:00

source checked

automated source review · 2026-09-16

Audit details

Targeted full-paper and supplement review of the outstanding task fields, with original dataset metadata checked where accessible. Source-scoped omissions are explicit; no independent benchmark reproduction or numerical-result change.

Field: attributes.profile.diagram.steps

Source artifact SHA-256: ef6c68f5c9b47c2f89598ddf647f05b72e4155e8b33609ebff23936a84bbd41d

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

Inspected artifact

Diagram title

Computational evaluation flow

Individual claims
Mouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility

Original source ↗

Results: cross-species human cell classification; cached text line 41; Materials and methods: Human cell type classification using mouse-Geneformer; Table 4

Version: version of record
Retrieved: 2026-09-16T10:44:03.392488+00:00

source checked

automated source review · 2026-09-16

Audit details

Targeted full-paper and supplement review of the outstanding task fields, with original dataset metadata checked where accessible. Source-scoped omissions are explicit; no independent benchmark reproduction or numerical-result change.

Field: attributes.profile.diagram.title

Source artifact SHA-256: ef6c68f5c9b47c2f89598ddf647f05b72e4155e8b33609ebff23936a84bbd41d

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

Inspected artifact

Datasets

Human thymus scRNA-seq data from GSE144870, alongside separate breast and cortex evaluations.

Individual claims
Mouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility

Original source ↗

Results: cross-species human cell classification; cached text line 41

Version: version of record
Retrieved: 2026-09-16T10:44:03.392488+00:00

source checked

automated source review · 2026-09-16

Audit details

Targeted full-paper and supplement review of the outstanding task fields, with original dataset metadata checked where accessible. Source-scoped omissions are explicit; no independent benchmark reproduction or numerical-result change.

Field: attributes.profile.facts.0.value

Source artifact SHA-256: ef6c68f5c9b47c2f89598ddf647f05b72e4155e8b33609ebff23936a84bbd41d

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

Inspected artifact

Splits

Human thymus cells come from GSE144870. After mapping human genes to mouse homologues, the fine-tuning experiment randomly uses 80% of cells for training and 20% for testing; the zero-shot column is a separate evaluation setting.

Individual claims
Mouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility

Original source ↗

Materials and methods: Human cell type classification using mouse-Geneformer; Table 4

Version: version of record
Retrieved: 2026-09-16T10:44:03.392488+00:00

source checked

automated source review · 2026-09-16

Audit details

Targeted full-paper and supplement review of the outstanding task fields, with original dataset metadata checked where accessible. Source-scoped omissions are explicit; no independent benchmark reproduction or numerical-result change.

Field: attributes.profile.facts.1.value

Source artifact SHA-256: ef6c68f5c9b47c2f89598ddf647f05b72e4155e8b33609ebff23936a84bbd41d

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

Inspected artifact

Adaptation

Cross-species representation transfer compared with the human Geneformer baseline.

Individual claims
Mouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility

Original source ↗

Results: cross-species human cell classification; cached text line 41

Version: version of record
Retrieved: 2026-09-16T10:44:03.392488+00:00

source checked

automated source review · 2026-09-16

Audit details

Targeted full-paper and supplement review of the outstanding task fields, with original dataset metadata checked where accessible. Source-scoped omissions are explicit; no independent benchmark reproduction or numerical-result change.

Field: attributes.profile.facts.10.value

Source artifact SHA-256: ef6c68f5c9b47c2f89598ddf647f05b72e4155e8b33609ebff23936a84bbd41d

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

Inspected artifact

Metrics

Cell-type classification accuracy.

Individual claims
Mouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility

Original source ↗

Results: cross-species human cell classification; cached text line 41

Version: version of record
Retrieved: 2026-09-16T10:44:03.392488+00:00

source checked

automated source review · 2026-09-16

Audit details

Targeted full-paper and supplement review of the outstanding task fields, with original dataset metadata checked where accessible. Source-scoped omissions are explicit; no independent benchmark reproduction or numerical-result change.

Field: attributes.profile.facts.2.value

Source artifact SHA-256: ef6c68f5c9b47c2f89598ddf647f05b72e4155e8b33609ebff23936a84bbd41d

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

Inspected artifact

Baselines

Mouse-Geneformer and human Geneformer.

Individual claims
Mouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility

Original source ↗

Results: cross-species human cell classification; cached text line 41

Version: version of record
Retrieved: 2026-09-16T10:44:03.392488+00:00

source checked

automated source review · 2026-09-16

Audit details

Targeted full-paper and supplement review of the outstanding task fields, with original dataset metadata checked where accessible. Source-scoped omissions are explicit; no independent benchmark reproduction or numerical-result change.

Field: attributes.profile.facts.3.value

Source artifact SHA-256: ef6c68f5c9b47c2f89598ddf647f05b72e4155e8b33609ebff23936a84bbd41d

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

Inspected artifact

Leakage controls

The source states these datasets are outside Genecorpus-30M; this review does not treat its feature-distance check as proof of complete leakage absence.

Individual claims
Mouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility

Original source ↗

Results: cross-species human cell classification; cached text line 41

Version: version of record
Retrieved: 2026-09-16T10:44:03.392488+00:00

source checked

automated source review · 2026-09-16

Audit details

Targeted full-paper and supplement review of the outstanding task fields, with original dataset metadata checked where accessible. Source-scoped omissions are explicit; no independent benchmark reproduction or numerical-result change.

Field: attributes.profile.facts.4.value

Source artifact SHA-256: ef6c68f5c9b47c2f89598ddf647f05b72e4155e8b33609ebff23936a84bbd41d

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

Inspected artifact

Uncertainty

Table 4 prints one accuracy and F1 value per model/setting. Its caption and the human classification method do not report confidence intervals, standard deviations or repeated-split uncertainty for the thymus result.

Individual claims
Mouse-Geneformer: A deep learning model for mouse single-cell transcriptome and its cross-species utility

Original source ↗

Materials and methods: Human cell type classification using mouse-Geneformer; Table 4 caption

Version: version of record
Retrieved: 2026-09-16T10:44:03.392488+00:00

unreported

automated source review · 2026-09-16

Audit details

Targeted full-paper and supplement review of the outstanding task fields, with original dataset metadata checked where accessible. Source-scoped omissions are explicit; no independent benchmark reproduction or numerical-result change.

Field: attributes.profile.facts.5.value

Source artifact SHA-256: ef6c68f5c9b47c2f89598ddf647f05b72e4155e8b33609ebff23936a84bbd41d

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-031186b57c62de

areas
cells-tissues
tasks
Human thymus cell-type classification
entity level
task
version
Not reported
task
Human thymus cell-type classification
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-mouse-geneformer-2025; inspected locators: Table 4 and footnote; Methods: Cell type classification; Methods: Cross-species application; searched queries: "mouse" "Geneformer" "PMC11964219"; gaps: Only the thymus row belongs to the assigned benchmark; cortex and breast must be separate protocols.; The authors' Euclidean nonidentity check is not proof that all leakage is absent; source wording must not become an independently established guarantee.; No replicate uncertainty in Table 4.; 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: mouse-geneformer-2025; source locator: Results: cross-species human cell classification; cached text line 41; 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.
Related records

Suggest a correction