Model type
Single-cell foundation model; this record is the paper-specific evaluated configuration.
scGPT is a learned-expression comparator in the GenePT study.
Conceptual input–method–output guide. Check the procedure text and linked evaluation for fitted components, additional inputs and exact settings.
Single-cell foundation model; this record is the paper-specific evaluated configuration.
Single-cell gene-expression profiles
Pretrained gene/cell representations and task-specific predictions
Official upstream implementation and usage documentation: https://github.com/bowang-lab/scGPT/blob/cebd6fae655b9c585a4807daa3ac31bb764f06b4/README.md. This pinned documentation revision is not automatically the evaluated weight revision.
limited source coverage · Automated source review, 2026-09-23. All specifications and missing details
1 evaluation · 1 result. Different protocols are not a single leaderboard.
Applied filters: All linked evaluations
| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: scGPT | Task: Cell-type structure in frozen embeddings Dataset: Aorta single-cell dataset | 0.47 Adjusted Rand Index unitless · unknown Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourcescGPT: Cell-type structure in frozen embeddings k-means on pretrained cell embeddings; agreement with original cell-type labels. Aggregation: Not reported GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT · Table 2, Aorta / Cell type row, scGPT ARI column |
Source checking is not independent reproduction. Release 2026-09-29-06401fd5b220.
Related profile: scGPT. This page retains the exact record and its evaluation context.
The study uses pretrained scGPT gene/cell embeddings for downstream applications, including previously documented gene-level results and extracted cell-level features.
The official scGPT implementation supplies pretrained checkpoints and separate workflows for embedding extraction, cell annotation, integration and perturbation modelling. The checkpoint and adaptation procedure must be identified separately for each result.
The linked evaluation record identifies scGPT: Cell-type structure in frozen embeddings. Its dataset, split, adaptation and evidence origin remain attached to the reported results.
Follow-up review of Known versions / configuration. Source locations and before/after decisions are recorded in the 23 September profile-evidence audit. Other explanatory content retains its earlier source scope. No human scientific review or independent reproduction is implied.
Stable record: reported-model-399b1ce87a3f6dExplanatory profile: limited source coverage · Automated source review, 2026-09-23. Review applies to the cited claims; unresolved fields are listed below. Numerical results retain their own review status.
| Property | Description and evidence |
|---|---|
| Model type | Single-cell foundation model; this record is the paper-specific evaluated configuration.Sourcesbowang-lab/scGPT README.md · README.md model description |
| Architecture / procedure | The study uses pretrained scGPT gene/cell embeddings for downstream applications, including previously documented gene-level results and extracted cell-level features.SourcesGenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT · Methods/Downstream gene-level and cell-level applications: (paragraph 1); Methods/Data Collection and Transformation: (paragraph 1) |
| Biological inputs | Single-cell gene-expression profilesSourcesGenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT · Related Work/Deciphering natural language embeddings (paragraph 5); Abstract (paragraph 1) |
| Outputs | Pretrained gene/cell representations and task-specific predictionsSourcesGenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT · Results/GenePT embeddings capture underlying gene functionality (paragraph 2); Methods/Downstream gene-level and cell-level applications: (paragraph 1) |
| Parameters | An aggregate parameter total for this exact evaluated configuration is not established by the inspected sources. · Not reported in inspected sourcesSources (2)GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT; bowang-lab/scGPT README.md · Methods/Data Collection and Transformation:; Methods/Downstream gene-level and cell-level applications:; inspected for aggregate parameter count (component sizes are not added without an exact configuration); README.md at pinned repository revision |
| Known versions / configuration | GenePT uses pretrained scGPT embeddings for cell-level evaluations and includes previously documented gene-level findings. The inspected methods do not pin an immutable scGPT weight revision; the family’s current whole-human download is not proof of historical identity. · Not reported in inspected sourcesSourcesGenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT · XML P10, P21 and P29-P30, evaluation methods. |
| Training data / fitting | The source describes scGPT pretraining on 33 million CELLxGENE cells; the reported comparator uses frozen embeddings and cosine 10-nearest-neighbour classification.SourcesGenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT · Related Work / Foundation models for single-cell transcriptomics; Table4 |
| Context limits | A maximum input/context length for this exact evaluated configuration is not established by the inspected sources. · Not reported in inspected sourcesSources (2)GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT; bowang-lab/scGPT README.md · Methods/Data Collection and Transformation:; Methods/Downstream gene-level and cell-level applications:; inspected for explicit maximum input length (dataset lengths and family-wide limits are not substituted); README.md at pinned repository revision |
| Access | Official upstream implementation and usage documentation: https://github.com/bowang-lab/scGPT/blob/cebd6fae655b9c585a4807daa3ac31bb764f06b4/README.md. This pinned documentation revision is not automatically the evaluated weight revision.Sourcesbowang-lab/scGPT README.md · README.md; installation, model download and usage instructions |
| Code licence | MIT (upstream repository code at the cited revision; this does not establish every dependency or historical checkpoint licence).Sourcesbowang-lab/scGPT LICENSE · LICENSE; complete licence text |
| Weights licence | The inspected model-access documentation does not explicitly identify terms for this exact evaluated checkpoint or fitted head; repository code terms are shown separately. · Not reported in inspected sourcesSourcesbowang-lab/scGPT README.md · README.md; checkpoint/access documentation and licence scope |
Source checking verifies the cited claim or transcription. It does not establish independent reproduction.
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.
24 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Diagram caption Conceptual input–method–output guide. Check the procedure text and linked evaluation for fitted components, additional inputs and exact settings. Individual claims | GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT Methods/Downstream gene-level and cell-level applications: (paragraph 1); Methods/Data Collection and Transformation: (paragraph 1) Version: PMC archival version PMC10614824.2 | source checked automated source review · 2026-09-23 Audit detailsFollow-up review of Known versions / configuration. Source locations and before/after decisions are recorded in the 23 September profile-evidence audit. Other explanatory content retains its earlier source scope. No human scientific review or independent reproduction is implied. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Diagram steps
| GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT Methods/Downstream gene-level and cell-level applications: (paragraph 1); Methods/Data Collection and Transformation: (paragraph 1) Version: PMC archival version PMC10614824.2 | source checked automated source review · 2026-09-23 Audit detailsFollow-up review of Known versions / configuration. Source locations and before/after decisions are recorded in the 23 September profile-evidence audit. Other explanatory content retains its earlier source scope. No human scientific review or independent reproduction is implied. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Diagram title Evaluated procedure (conceptual) Individual claims | GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT Methods/Downstream gene-level and cell-level applications: (paragraph 1); Methods/Data Collection and Transformation: (paragraph 1) Version: PMC archival version PMC10614824.2 | source checked automated source review · 2026-09-23 Audit detailsFollow-up review of Known versions / configuration. Source locations and before/after decisions are recorded in the 23 September profile-evidence audit. Other explanatory content retains its earlier source scope. No human scientific review or independent reproduction is implied. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Model type Single-cell foundation model; this record is the paper-specific evaluated configuration. Individual claims | bowang-lab/scGPT README.md README.md model description Version: cebd6fae655b9c585a4807daa3ac31bb764f06b4 | source checked automated source review · 2026-09-23 Audit detailsFollow-up review of Known versions / configuration. Source locations and before/after decisions are recorded in the 23 September profile-evidence audit. Other explanatory content retains its earlier source scope. No human scientific review or independent reproduction is implied. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Architecture / procedure The study uses pretrained scGPT gene/cell embeddings for downstream applications, including previously documented gene-level results and extracted cell-level features. Individual claims | GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT Methods/Downstream gene-level and cell-level applications: (paragraph 1); Methods/Data Collection and Transformation: (paragraph 1) Version: PMC archival version PMC10614824.2 | source checked automated source review · 2026-09-23 Audit detailsFollow-up review of Known versions / configuration. Source locations and before/after decisions are recorded in the 23 September profile-evidence audit. Other explanatory content retains its earlier source scope. No human scientific review or independent reproduction is implied. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Weights licence The inspected model-access documentation does not explicitly identify terms for this exact evaluated checkpoint or fitted head; repository code terms are shown separately. Individual claims | bowang-lab/scGPT README.md README.md; checkpoint/access documentation and licence scope Version: cebd6fae655b9c585a4807daa3ac31bb764f06b4 | unreported automated source review · 2026-09-23 Audit detailsFollow-up review of Known versions / configuration. Source locations and before/after decisions are recorded in the 23 September profile-evidence audit. Other explanatory content retains its earlier source scope. No human scientific review or independent reproduction is implied. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Biological inputs Single-cell gene-expression profiles Individual claims | GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT Related Work/Deciphering natural language embeddings (paragraph 5); Abstract (paragraph 1) Version: PMC archival version PMC10614824.2 | source checked automated source review · 2026-09-23 Audit detailsFollow-up review of Known versions / configuration. Source locations and before/after decisions are recorded in the 23 September profile-evidence audit. Other explanatory content retains its earlier source scope. No human scientific review or independent reproduction is implied. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Outputs Pretrained gene/cell representations and task-specific predictions Individual claims | GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT Results/GenePT embeddings capture underlying gene functionality (paragraph 2); Methods/Downstream gene-level and cell-level applications: (paragraph 1) Version: PMC archival version PMC10614824.2 | source checked automated source review · 2026-09-23 Audit detailsFollow-up review of Known versions / configuration. Source locations and before/after decisions are recorded in the 23 September profile-evidence audit. Other explanatory content retains its earlier source scope. No human scientific review or independent reproduction is implied. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Parameters An aggregate parameter total for this exact evaluated configuration is not established by the inspected sources. Individual claims | bowang-lab/scGPT README.md Methods/Data Collection and Transformation:; Methods/Downstream gene-level and cell-level applications:; inspected for aggregate parameter count (component sizes are not added without an exact configuration); README.md at pinned repository revision Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: cebd6fae655b9c585a4807daa3ac31bb764f06b4 | unreported automated source review · 2026-09-23 Audit detailsFollow-up review of Known versions / configuration. Source locations and before/after decisions are recorded in the 23 September profile-evidence audit. Other explanatory content retains its earlier source scope. No human scientific review or independent reproduction is implied. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Parameters An aggregate parameter total for this exact evaluated configuration is not established by the inspected sources. Individual claims | GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT Methods/Data Collection and Transformation:; Methods/Downstream gene-level and cell-level applications:; inspected for aggregate parameter count (component sizes are not added without an exact configuration); README.md at pinned repository revision Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: PMC archival version PMC10614824.2 | unreported automated source review · 2026-09-23 Audit detailsFollow-up review of Known versions / configuration. Source locations and before/after decisions are recorded in the 23 September profile-evidence audit. Other explanatory content retains its earlier source scope. No human scientific review or independent reproduction is implied. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
View linked audit checks and correction history
Release 2026-09-29-06401fd5b220 · Record review: needs review
Stable ID: reported-model-399b1ce87a3f6d