Model type
Study-specific predictive method; this record is the paper-specific evaluated configuration.
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)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)At a glance
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)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.
| Metric and finding | Coverage and uncertainty | Evidence |
|---|---|---|
| GenePT-w: Cell-type structure in frozen embeddings Configuration: GenePT-wTask: Cell-type structure in frozen embeddingsDataset: Aorta single-cell dataset k-means on pretrained cell embeddings; agreement with original cell-type labels. Author-reported evaluation · Evaluation metadata: needs review | ||
| 0.54 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, GenePT-w ARI column Source checking is not independent reproduction. |
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
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)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-b3-011Strengths 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-7c595040de69bcSpecifications
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.
| Property | Description and evidence |
|---|---|
| Model type | Study-specific predictive method; this record is the paper-specific evaluated configuration.SourcesGenePT: 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.SourcesGenePT: 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 valuesSourcesGenePT: 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 tasksSourcesGenePT: 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 sourcesSources (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 sourcesSourcesGenePT: 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.SourcesGenePT: 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 sourcesSources (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.Sourcesyiqunchen/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 sourcesSourcesyiqunchen/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 sourcesSourcesyiqunchen/GenePT 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.
21 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/Data Collection and Transformation: (paragraph 4); Related Work/Using language models for cell biology (paragraph 1) Version: PMC archival version PMC10614824.2 | source checked automated source review · 2026-09-16 Audit detailsPrimary 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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| 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 Methods/Data Collection and Transformation: (paragraph 4); Related Work/Using language models for cell biology (paragraph 1) Version: PMC archival version PMC10614824.2 | source checked automated source review · 2026-09-16 Audit detailsPrimary 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: 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/Data Collection and Transformation: (paragraph 4); Related Work/Using language models for cell biology (paragraph 1) Version: PMC archival version PMC10614824.2 | source checked automated source review · 2026-09-16 Audit detailsPrimary 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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| 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 Methods/Data Collection and Transformation: (paragraph 4); Related Work/Using language models for cell biology (paragraph 1) Version: PMC archival version PMC10614824.2 | source checked automated source review · 2026-09-16 Audit detailsPrimary 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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| 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 Methods/Data Collection and Transformation: (paragraph 4); Related Work/Using language models for cell biology (paragraph 1) Version: PMC archival version PMC10614824.2 | source checked automated source review · 2026-09-16 Audit detailsPrimary 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: 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 | yiqunchen/GenePT README.md README.md; checkpoint/access documentation and licence scope Version: 3602699e7425a7be577771f8f07e218db6c79b9f | unreported automated source review · 2026-09-16 Audit detailsPrimary 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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| 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 Related Work/Deciphering natural language embeddings (paragraph 4); Related Work/Deciphering natural language embeddings (paragraph 5) Version: PMC archival version PMC10614824.2 | source checked automated source review · 2026-09-16 Audit detailsPrimary 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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Outputs Cell embeddings for downstream cell-analysis tasks Individual claims | 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) Version: PMC archival version PMC10614824.2 | source checked automated source review · 2026-09-16 Audit detailsPrimary 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: 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 | 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 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 3602699e7425a7be577771f8f07e218db6c79b9f | unreported automated source review · 2026-09-16 Audit detailsPrimary 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: 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 · 2026-09-16 Audit detailsPrimary 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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Sources and history
Release 2026-09-17-d277315f7d76 · 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
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.