Configuration

GenePT-w

GenePT-w represents cells by expression-weighted averages of gene embeddings derived from gene-description text.

Sources

GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT · Introduction (paragraph 4); Methods/Data Collection and Transformation: (paragraph 2)

1 evaluation · 1 result

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/Data Collection and Transformation: (paragraph 4); Related Work/Using language models for cell biology (paragraph 1)

Overview

Model type

Study-specific predictive method; this record is the paper-specific evaluated configuration.

Sources

Biological inputs

Gene-description embeddings and single-cell expression values

Sources

GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT · Related Work/Deciphering natural language embeddings (paragraph 4); Related Work/Deciphering natural language embeddings (paragraph 5)

Outputs

Cell embeddings for downstream cell-analysis tasks

Sources

GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT · Related Work/Deciphering natural language embeddings (paragraph 4); Methods/Downstream gene-level and cell-level applications: (paragraph 1)

Access

Official study implementation and usage documentation: https://github.com/yiqunchen/GenePT/blob/3602699e7425a7be577771f8f07e218db6c79b9f/README.md. This pinned documentation revision is not automatically the evaluated weight revision.

Sources

yiqunchen/GenePT README.md · README.md; installation, model download and usage instructions

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

Evaluations and results

1 evaluation · 1 result. Different protocols are not a single leaderboard.

Filter evaluations

Tested model or methodProtocolDatasetEvaluation setupMetricEvidence origin

Applied filters: All linked evaluations

Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: GenePT-w	Task: Cell-type structure in frozen embeddings Dataset: Aorta single-cell dataset	0.54 Adjusted Rand Index unitless · unknown Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source GenePT-w: 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, GenePT-w ARI column

Source checking is not independent reproduction. Release 2026-09-29-06401fd5b220.

Use this model

How it works, versions and access

How it works

How the evaluated method works

Gene descriptions from NCBI are embedded using GPT-3.5. The weighted variant averages gene vectors according to each cell’s expression values; it differs from the sentence-embedding variant.

Sources

What was evaluated

The linked evaluation record identifies GenePT-w: 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-b3-011

Strengths, limitations and unresolved questions

Strengths and limitations

Strengths and considerations

Provides a relatively simple literature-derived representation baseline for single-cell tasks.
Sources
GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT · Results/GenePT learns representations that reflect cell biology (paragraph 2); Appendix/Appendix C Cell type annotation results (paragraph 1)

Limitations and conditions

Depends on coverage and content of gene annotations and a proprietary text-embedding model; it is not a direct measurement of molecular mechanism.
Sources
GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT · Appendix/Appendix B Additional results for the gene level functionality and property predictions/B.3 Addressing potential information leakage/B.5 Experiments with tissue-dependent gene emebddings (paragraph 4); Methods/Data Collection and Transformation: (paragraph 1)

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-7c595040de69bc

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	Study-specific predictive method; this record is the paper-specific evaluated configuration. Sources GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT · Methods/Data Collection and Transformation: (paragraph 4); Related Work/Using language models for cell biology (paragraph 1)
Architecture / procedure	Gene descriptions from NCBI are embedded using GPT-3.5. The weighted variant averages gene vectors according to each cell’s expression values; it differs from the sentence-embedding variant. Sources GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT · Methods/Data Collection and Transformation: (paragraph 4); Related Work/Using language models for cell biology (paragraph 1)
Biological inputs	Gene-description embeddings and single-cell expression values Sources GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT · Related Work/Deciphering natural language embeddings (paragraph 4); Related Work/Deciphering natural language embeddings (paragraph 5)
Outputs	Cell embeddings for downstream cell-analysis tasks Sources GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT · Related Work/Deciphering natural language embeddings (paragraph 4); 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; yiqunchen/GenePT 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-w 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 biological representation uses NCBI gene descriptions; the method does not train a new foundation model on a large cell-expression corpus. Sources GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT · Abstract (paragraph 1); Introduction (paragraph 4)
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; yiqunchen/GenePT 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 study implementation and usage documentation: https://github.com/yiqunchen/GenePT/blob/3602699e7425a7be577771f8f07e218db6c79b9f/README.md. This pinned documentation revision is not automatically the evaluated weight revision. Sources yiqunchen/GenePT README.md · README.md; installation, model download and usage instructions
Code licence	No explicit code licence was established from the paper’s availability statement and inspected repository-root documentation. · Not reported in inspected sources Sources yiqunchen/GenePT README.md · README.md and repository-root licence-file search
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 yiqunchen/GenePT README.md · README.md; checkpoint/access documentation and licence scope

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.

21 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-09-29-06401fd5b220
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/Data Collection and Transformation: (paragraph 4); Related Work/Using language models for cell biology (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 Gene-description embeddings and single-cell expression values GenePT-w Cell embeddings for downstream cell-analysis tasks Individual claims	GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT Original source ↗ Methods/Data Collection and Transformation: (paragraph 4); Related Work/Using language models for cell biology (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/Data Collection and Transformation: (paragraph 4); Related Work/Using language models for cell biology (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 Study-specific predictive method; this record is the paper-specific evaluated configuration. Individual claims	GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT Original source ↗ Methods/Data Collection and Transformation: (paragraph 4); Related Work/Using language models for cell biology (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.0.value` Source artifact SHA-256: `230a2ec55458d9243eaeeebf3244df7409eb02d47f4b809ee56a06dcb6fdd047` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Architecture / procedure Gene descriptions from NCBI are embedded using GPT-3.5. The weighted variant averages gene vectors according to each cell’s expression values; it differs from the sentence-embedding variant. Individual claims	GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT Original source ↗ Methods/Data Collection and Transformation: (paragraph 4); Related Work/Using language models for cell biology (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	yiqunchen/GenePT README.md Original source ↗ README.md; checkpoint/access documentation and licence scope Version: 3602699e7425a7be577771f8f07e218db6c79b9f Retrieved: 2026-09-16T19:54:16.422790+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: `8740cf98377f964131399de818db5de938db4d9e6abe20fac3cd0354887a99c2` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Biological inputs Gene-description embeddings and single-cell expression values 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 4); Related Work/Deciphering natural language embeddings (paragraph 5) 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 Cell embeddings for downstream cell-analysis tasks 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 4); 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	yiqunchen/GenePT 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: 3602699e7425a7be577771f8f07e218db6c79b9f Retrieved: 2026-09-16T19:54:16.422790+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: `8740cf98377f964131399de818db5de938db4d9e6abe20fac3cd0354887a99c2` 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

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Release 2026-09-29-06401fd5b220 · Record review: needs review

2 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
yiqunchen/GenePT README.md · Original source · 3602699e7425a7be577771f8f07e218db6c79b9f

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Technical metadata and extraction receipts

Stable ID: reported-model-7c595040de69bc

areas: cells-tissues
entity level: method
version: Not reported
reported name: GenePT-w
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; source locator: Methods/Data Collection and Transformation: (paragraph 4); Related Work/Using language models for cell biology (paragraph 1) | Introduction (paragraph 4); Methods/Data Collection and Transformation: (paragraph 2); 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: GenePT-w: Cell-type structure in frozen embeddings

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