model · method

scGPT

scGPT is the method recorded for Cell-type annotation. This page preserves the configuration reported by scELMo: Embeddings from Language Models are Good Learners for Single-cell Data Analysis.

1 evaluations · 1 metric rows

At a glance

Explanatory profile: limited source coverage · Automated source review, 2026-09-16. This does not change the review status of its results.

Inputs, outputs and configuration
Property	Description and evidence
Recorded dataset	hPancreasscELMo: Embeddings from Language Models are Good Learners for Single-cell Data Analysis · Table 1, hPancreas zero-shot / scGPT (z) row, F1 column
Model type	Not extracted or verified for this record.
Known versions	Not extracted or verified for this record.
Training data	Not extracted or verified for this record.
Context limits	Not extracted or verified for this record.
Access	Not extracted or verified for this record.
Code licence	Not extracted or verified for this record.
Weights licence	Not extracted or verified for this record.

How it works

Recorded evaluation

The imported evaluation describes this procedure: Zero-shot setting; source caption says some comparator rows come from GenePT.

scELMo: Embeddings from Language Models are Good Learners for Single-cell Data Analysis · Table 1, hPancreas zero-shot / scGPT (z) row, F1 column

Benchmarks and results

Release 2026-09-16-d74d282221a9 · 1 evaluation · 1 metric row. Different protocols are not a single leaderboard.

Evaluated configurationMetricEvidence origin

Results grouped by the exact reported evaluation
Metric and finding	Coverage and uncertainty	Evidence
scGPT: Cell-type annotation Model: scGPT · Benchmark: Cell-type annotation · Dataset: hPancreas Zero-shot setting; source caption says some comparator rows come from GenePT. Result quoted from another source · Evaluation metadata: needs review
0.550 F1 Unit: unitless · Direction: unknown	Uncertainty: not reported in legacy extract Scored: Not reported · Eligible: Not reported	source checkedscELMo: Embeddings from Language Models are Good Learners for Single-cell Data Analysis · Table 1, hPancreas zero-shot / scGPT (z) row, F1 column Source checking is not independent reproduction.

Strengths and limitations

Strengths and considerations

No source-reviewed explanatory claims are recorded here yet.

Limitations and conditions

This is an evidence-limited profile. The recorded evaluation context does not establish performance on other datasets or configurations.scELMo: Embeddings from Language Models are Good Learners for Single-cell Data Analysis · Table 1, hPancreas zero-shot / scGPT (z) row, F1 column

Profile review details

Reviewed the existing release record, its source pointer and linked evaluation context. This is not a fresh full-text architecture review or independent reproduction; numerical review status is unchanged.

Stable record: reported-model-77ad27d4098177

Sources and history

Release 2026-09-16-d74d282221a9 · Record review: needs review

scELMo: Embeddings from Language Models are Good Learners for Single-cell Data Analysis · Original source · preprint archived 2025-08-23

Download this release

Technical metadata and extraction receipts

Stable ID: reported-model-77ad27d4098177

areas: cells-tissues
entity level: method
version: Not reported
reported name: scGPT
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

Related records

model: scGPT: Cell-type annotation

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