Configuration

scGPT

scGPT is a learned-expression comparator in the GenePT study.

Sources

GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT · Results/GenePT embedding removes batch effect while preserving underlying biology (paragraph 1); Abstract (paragraph 1)

1 evaluation · 1 metric row

How it worksEvaluated procedure (conceptual)

Conceptual input–method–output guide. Check the procedure text and linked evaluation for fitted components, additional inputs and exact settings.

Sources

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)

At a glance

Model type

Single-cell foundation model; this record is the paper-specific evaluated configuration.

Sources

bowang-lab/scGPT README.md · README.md model description

Biological inputs

Single-cell gene-expression profiles

Sources

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)

Outputs

Pretrained gene/cell representations and task-specific predictions

Sources

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)

limited source coverage · Automated source review, 2026-09-16. All specifications and missing details

Evaluations and results

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

Evaluation setupMetricEvidence origin

Results grouped by the exact reported evaluation
Metric and finding	Coverage and uncertainty	Evidence
scGPT: Cell-type structure in frozen embeddings Configuration: scGPTTask: Cell-type structure in frozen embeddingsDataset: Aorta single-cell dataset k-means on pretrained cell embeddings; agreement with original cell-type labels. Independent external evaluation · Evaluation metadata: needs review
0.47 Adjusted Rand Index Unit: unitless · Direction: unknown	Uncertainty: not reported in legacy extract Scored: Not reported · Eligible: Not reported	source checkedGenePT: 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.

How it works

How the evaluated method works

The study uses pretrained scGPT gene/cell embeddings for downstream applications, including previously documented gene-level results and extracted cell-level features.

Sources

Underlying method and version boundaries

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.

Sources

bowang-lab/scGPT README.md · README.md; introduction, model description, pretrained-model and usage sections at pinned revision

What was evaluated

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.

Sources

GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT · The named evaluation’s methods and comparison table; exact preserved evaluation IDs: evaluation-lit-b3-012

Strengths and limitations

Strengths and considerations

Provides an expression-pretraining reference against text-derived GenePT embeddings.
Sources
GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT · Methods/Data Collection and Transformation: (paragraph 2); Introduction (paragraph 4)

Limitations and conditions

Some gene-level comparator scores are drawn from previous documentation; they are not all freshly trained or independently replicated by this study.
Sources
GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT · Appendix/Appendix A Assessing GenePT sensitivity to variations in gene summary inputs (paragraph 2); Related Work/Deciphering natural language embeddings (paragraph 3)

Profile review details

Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction.

Stable record: reported-model-399b1ce87a3f6d

Specifications

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.

Inputs, outputs and configuration
Property	Description and evidence
Model type	Single-cell foundation model; this record is the paper-specific evaluated configuration. Sources bowang-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. Sources 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)
Biological inputs	Single-cell gene-expression profiles Sources 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)
Outputs	Pretrained gene/cell representations and task-specific predictions Sources 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)
Parameters	An aggregate parameter total for this exact evaluated configuration is not established by the inspected sources. · Not reported in inspected sources Sources (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	scGPT is the comparison-table label; that label does not specify an immutable weight revision. · Not reported in inspected sources Sources GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT · Model identification in the comparison table and corresponding Methods; immutable checkpoint revision is not supplied by the table label.
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. Sources GenePT: 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 sources Sources (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. Sources bowang-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). Sources bowang-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 sources Sources bowang-lab/scGPT README.md · README.md; checkpoint/access documentation and licence scope

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.

22 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-09-17-d277315f7d76
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 Original source ↗ Methods/Downstream gene-level and cell-level applications: (paragraph 1); Methods/Data Collection and Transformation: (paragraph 1) Version: PMC archival version PMC10614824.2 Retrieved: 2026-09-16T10:44:03.399274+00:00	source checked automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.diagram.caption` Source artifact SHA-256: `230a2ec55458d9243eaeeebf3244df7409eb02d47f4b809ee56a06dcb6fdd047` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Diagram steps ["Single-cell gene-expression profiles","scGPT","Pretrained gene/cell representations and task-specific predictions"] Individual claims	GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT Original source ↗ Methods/Downstream gene-level and cell-level applications: (paragraph 1); Methods/Data Collection and Transformation: (paragraph 1) Version: PMC archival version PMC10614824.2 Retrieved: 2026-09-16T10:44:03.399274+00:00	source checked automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.diagram.steps` Source artifact SHA-256: `230a2ec55458d9243eaeeebf3244df7409eb02d47f4b809ee56a06dcb6fdd047` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Diagram title Evaluated procedure (conceptual) Individual claims	GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT Original source ↗ Methods/Downstream gene-level and cell-level applications: (paragraph 1); Methods/Data Collection and Transformation: (paragraph 1) Version: PMC archival version PMC10614824.2 Retrieved: 2026-09-16T10:44:03.399274+00:00	source checked automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.diagram.title` Source artifact SHA-256: `230a2ec55458d9243eaeeebf3244df7409eb02d47f4b809ee56a06dcb6fdd047` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Model type Single-cell foundation model; this record is the paper-specific evaluated configuration. Individual claims	bowang-lab/scGPT README.md Original source ↗ README.md model description Version: cebd6fae655b9c585a4807daa3ac31bb764f06b4 Retrieved: 2026-09-16T20:00:00.816587+00:00	source checked automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.facts.0.value` Source artifact SHA-256: `b0503e8ca789f19f1fc2350c5aaf57b1b323bbae43b354655231b5f4a1586c83` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
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 Original source ↗ Methods/Downstream gene-level and cell-level applications: (paragraph 1); Methods/Data Collection and Transformation: (paragraph 1) Version: PMC archival version PMC10614824.2 Retrieved: 2026-09-16T10:44:03.399274+00:00	source checked automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.facts.1.value` Source artifact SHA-256: `230a2ec55458d9243eaeeebf3244df7409eb02d47f4b809ee56a06dcb6fdd047` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
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 Original source ↗ README.md; checkpoint/access documentation and licence scope Version: cebd6fae655b9c585a4807daa3ac31bb764f06b4 Retrieved: 2026-09-16T20:00:00.816587+00:00	unreported automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.facts.10.value` Source artifact SHA-256: `b0503e8ca789f19f1fc2350c5aaf57b1b323bbae43b354655231b5f4a1586c83` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Biological inputs Single-cell gene-expression profiles Individual claims	GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT Original source ↗ Related Work/Deciphering natural language embeddings (paragraph 5); Abstract (paragraph 1) Version: PMC archival version PMC10614824.2 Retrieved: 2026-09-16T10:44:03.399274+00:00	source checked automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.facts.2.value` Source artifact SHA-256: `230a2ec55458d9243eaeeebf3244df7409eb02d47f4b809ee56a06dcb6fdd047` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
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 Original source ↗ 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 Retrieved: 2026-09-16T10:44:03.399274+00:00	source checked automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.facts.3.value` Source artifact SHA-256: `230a2ec55458d9243eaeeebf3244df7409eb02d47f4b809ee56a06dcb6fdd047` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Parameters An aggregate parameter total for this exact evaluated configuration is not established by the inspected sources. Individual claims	bowang-lab/scGPT README.md Original source ↗ 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 Retrieved: 2026-09-16T20:00:00.816587+00:00	unreported automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.facts.4.value` Source artifact SHA-256: `b0503e8ca789f19f1fc2350c5aaf57b1b323bbae43b354655231b5f4a1586c83` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
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 Original source ↗ 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 Retrieved: 2026-09-16T10:44:03.399274+00:00	unreported automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.facts.4.value` Source artifact SHA-256: `230a2ec55458d9243eaeeebf3244df7409eb02d47f4b809ee56a06dcb6fdd047` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact

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Sources and history

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

3 source records and release history

GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT · Original source · PMC archival version PMC10614824.2
bowang-lab/scGPT README.md · Original source · cebd6fae655b9c585a4807daa3ac31bb764f06b4
bowang-lab/scGPT LICENSE · Original source · cebd6fae655b9c585a4807daa3ac31bb764f06b4

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Technical metadata and extraction receipts

Stable ID: reported-model-399b1ce87a3f6d

areas: cells-tissues
entity level: method
version: Not reported
reported name: scGPT
historical missing metadata: version: not_reported_in_legacy_extract; checkpoint revision: not_reported_in_legacy_extract; training data: not_reported_in_legacy_extract; licence: 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: model
entity classification: review date: 2026-09-17; rationale: This source-scoped entry preserves the method/configuration actually named in an evaluation. It is neither a global family identity nor proof of an immutable checkpoint; the linked evaluation retains adaptation, fitting and scoring details.; source ids: genept-2024; evidence-reported-base-scgpt-readme-md; source locator: Methods/Downstream gene-level and cell-level applications: (paragraph 1); Methods/Data Collection and Transformation: (paragraph 1) | README.md model description | Results/GenePT embedding removes batch effect while preserving underlying biology (paragraph 1); Abstract (paragraph 1); ambiguities: Configuration means the source-labelled evaluated identity. It does not establish missing checkpoint hashes, default settings or equivalence to same-named records in other papers.

Related records

model: scGPT: Cell-type structure in frozen embeddings

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