Evaluation

scGPT-spatial on Chen et al. 2026 zero-shot cell type and spatial domain clustering, BC

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Evaluation results

1 evaluation · 3 results. Different protocols are not a single leaderboard.

Protocol: Chen et al. 2026 zero-shot cell type and spatial domain clustering, BC · Dataset subset: BC (Chen et al. 2026)

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Tested configuration	Adjusted rand index	Normalized mutual information	Silhouette score (against reference labels on the model embedding; range -1 to 1; distance stated as cosine in some model sections of the Methods)
scGPT-spatial (zero-shot, Chen et al. 2026)Evaluation	0.28	0.45	0.09

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Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: scGPT-spatial (zero-shot, Chen et al. 2026)	Protocol: Chen et al. 2026 zero-shot cell type and spatial domain clustering, BC Dataset subset: BC (Chen et al. 2026)	0.28 Adjusted rand index unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons Table 4 precision and recall equal accuracy in all eight Nicheformer and CellPLM rows, as micro (global) averaging would give, but recall differs from accuracy in every scGPT-spatial, GenePT-w, scELMo and Novae row. The Methods call precision and recall 'global' without defining the averaging, so they may be averaged differently between models and should not be compared across models.Harmonised benchmarking of foundation models for single-cell and spatial transcriptomics reveals context-dependent generalisation · Table 4, columns 'Accuracy', 'Precision' and 'Recall'; Methods 'Cell type annotation' (page 25) Methods, coverage and source scGPT-spatial on Chen et al. 2026 zero-shot cell type and spatial domain clustering, BC lit-cells-networks-20261011-chen2026-protocol-zs-cluster-bc Aggregation: Not reported Harmonised benchmarking of foundation models for single-cell and spatial transcriptomics reveals context-dependent generalisation · Table 2, model 'scGPT-spatial', dataset 'BC', column 'ARI'
Configuration: scGPT-spatial (zero-shot, Chen et al. 2026)	Protocol: Chen et al. 2026 zero-shot cell type and spatial domain clustering, BC Dataset subset: BC (Chen et al. 2026)	0.45 Normalized mutual information unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons Table 4 precision and recall equal accuracy in all eight Nicheformer and CellPLM rows, as micro (global) averaging would give, but recall differs from accuracy in every scGPT-spatial, GenePT-w, scELMo and Novae row. The Methods call precision and recall 'global' without defining the averaging, so they may be averaged differently between models and should not be compared across models.Harmonised benchmarking of foundation models for single-cell and spatial transcriptomics reveals context-dependent generalisation · Table 4, columns 'Accuracy', 'Precision' and 'Recall'; Methods 'Cell type annotation' (page 25) Methods, coverage and source scGPT-spatial on Chen et al. 2026 zero-shot cell type and spatial domain clustering, BC lit-cells-networks-20261011-chen2026-protocol-zs-cluster-bc Aggregation: Not reported Harmonised benchmarking of foundation models for single-cell and spatial transcriptomics reveals context-dependent generalisation · Table 2, model 'scGPT-spatial', dataset 'BC', column 'NMI'
Configuration: scGPT-spatial (zero-shot, Chen et al. 2026)	Protocol: Chen et al. 2026 zero-shot cell type and spatial domain clustering, BC Dataset subset: BC (Chen et al. 2026)	0.09 Silhouette score (against reference labels on the model embedding; range -1 to 1; distance stated as cosine in some model sections of the Methods) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons Table 4 precision and recall equal accuracy in all eight Nicheformer and CellPLM rows, as micro (global) averaging would give, but recall differs from accuracy in every scGPT-spatial, GenePT-w, scELMo and Novae row. The Methods call precision and recall 'global' without defining the averaging, so they may be averaged differently between models and should not be compared across models.Harmonised benchmarking of foundation models for single-cell and spatial transcriptomics reveals context-dependent generalisation · Table 4, columns 'Accuracy', 'Precision' and 'Recall'; Methods 'Cell type annotation' (page 25) Methods, coverage and source scGPT-spatial on Chen et al. 2026 zero-shot cell type and spatial domain clustering, BC lit-cells-networks-20261011-chen2026-protocol-zs-cluster-bc Aggregation: Not reported Harmonised benchmarking of foundation models for single-cell and spatial transcriptomics reveals context-dependent generalisation · Table 2, model 'scGPT-spatial', dataset 'BC', column 'Silhouette'

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Evaluation procedure

Chen et al. 2026 zero-shot cell type and spatial domain clustering, BC

Configuration: scGPT-spatial (zero-shot, Chen et al. 2026)
Protocol: Chen et al. 2026 zero-shot cell type and spatial domain clustering, BC
Dataset subset: BC (Chen et al. 2026)

origin: Independent external evaluation
configuration: Primary source as retrieved 2026-10-11
protocol id: lit-cells-networks-20261011-chen2026-protocol-zs-cluster-bc
dataset version: Not reported
split: All cells (unsupervised clustering)
population: Not reported
inputs: Single-cell or spatial expression matrix, aligned to each model's gene vocabulary
adaptation: frozen pretrained embeddings, Leiden clustering with resolution tuned to the number of reference labels, seed 42
metric implementation: Not reported
aggregation: Not reported
budget: Not reported

Metadata review: source checked. Unreported conditions prevent automatic comparisons.

Reproduction

Split: All cells (unsupervised clustering)
Adaptation: frozen pretrained embeddings, Leiden clustering with resolution tuned to the number of reference labels, seed 42
Scoring implementation: Not reported

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18 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-10-23-5347695500ed
Property and statement	Original source and location	Review and provenance
Comparison: adaptation frozen pretrained embeddings, Leiden clustering with resolution tuned to the number of reference labels, seed 42 Context-only references	Harmonised benchmarking of foundation models for single-cell and spatial transcriptomics reveals context-dependent generalisation Original source ↗ Table 2, model 'scGPT-spatial', dataset 'BC' Version: arXiv 2607.17227v2, updated 2026-09-17 (v1 posted 2026-07-19) Retrieved: 2026-10-11T21:29:34Z	not individually reviewed No individual claim review recorded independent paper Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `attributes.comparison.adaptation` Source artifact SHA-256: `8137338c6146f570a6546f30707d4244baca9dab848b32c51539665a5ba539da` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison: aggregation Not reported Context-only references	Harmonised benchmarking of foundation models for single-cell and spatial transcriptomics reveals context-dependent generalisation Original source ↗ Table 2, model 'scGPT-spatial', dataset 'BC' Version: arXiv 2607.17227v2, updated 2026-09-17 (v1 posted 2026-07-19) Retrieved: 2026-10-11T21:29:34Z	missing or unspecified No individual claim review recorded independent paper Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `attributes.comparison.aggregation` Source artifact SHA-256: `8137338c6146f570a6546f30707d4244baca9dab848b32c51539665a5ba539da` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison: budget Not reported Context-only references	Harmonised benchmarking of foundation models for single-cell and spatial transcriptomics reveals context-dependent generalisation Original source ↗ Table 2, model 'scGPT-spatial', dataset 'BC' Version: arXiv 2607.17227v2, updated 2026-09-17 (v1 posted 2026-07-19) Retrieved: 2026-10-11T21:29:34Z	missing or unspecified No individual claim review recorded independent paper Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `attributes.comparison.budget` Source artifact SHA-256: `8137338c6146f570a6546f30707d4244baca9dab848b32c51539665a5ba539da` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison: dataset version Not reported Context-only references	Harmonised benchmarking of foundation models for single-cell and spatial transcriptomics reveals context-dependent generalisation Original source ↗ Table 2, model 'scGPT-spatial', dataset 'BC' Version: arXiv 2607.17227v2, updated 2026-09-17 (v1 posted 2026-07-19) Retrieved: 2026-10-11T21:29:34Z	missing or unspecified No individual claim review recorded independent paper Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `attributes.comparison.dataset_version` Source artifact SHA-256: `8137338c6146f570a6546f30707d4244baca9dab848b32c51539665a5ba539da` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison: inputs Single-cell or spatial expression matrix, aligned to each model's gene vocabulary Context-only references	Harmonised benchmarking of foundation models for single-cell and spatial transcriptomics reveals context-dependent generalisation Original source ↗ Table 2, model 'scGPT-spatial', dataset 'BC' Version: arXiv 2607.17227v2, updated 2026-09-17 (v1 posted 2026-07-19) Retrieved: 2026-10-11T21:29:34Z	not individually reviewed No individual claim review recorded independent paper Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `attributes.comparison.inputs` Source artifact SHA-256: `8137338c6146f570a6546f30707d4244baca9dab848b32c51539665a5ba539da` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison: metric implementation Not reported Context-only references	Harmonised benchmarking of foundation models for single-cell and spatial transcriptomics reveals context-dependent generalisation Original source ↗ Table 2, model 'scGPT-spatial', dataset 'BC' Version: arXiv 2607.17227v2, updated 2026-09-17 (v1 posted 2026-07-19) Retrieved: 2026-10-11T21:29:34Z	missing or unspecified No individual claim review recorded independent paper Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `attributes.comparison.metric_implementation` Source artifact SHA-256: `8137338c6146f570a6546f30707d4244baca9dab848b32c51539665a5ba539da` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison: population Not reported Context-only references	Harmonised benchmarking of foundation models for single-cell and spatial transcriptomics reveals context-dependent generalisation Original source ↗ Table 2, model 'scGPT-spatial', dataset 'BC' Version: arXiv 2607.17227v2, updated 2026-09-17 (v1 posted 2026-07-19) Retrieved: 2026-10-11T21:29:34Z	missing or unspecified No individual claim review recorded independent paper Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `attributes.comparison.population` Source artifact SHA-256: `8137338c6146f570a6546f30707d4244baca9dab848b32c51539665a5ba539da` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison: protocol id lit-cells-networks-20261011-chen2026-protocol-zs-cluster-bc Context-only references	Harmonised benchmarking of foundation models for single-cell and spatial transcriptomics reveals context-dependent generalisation Original source ↗ Table 2, model 'scGPT-spatial', dataset 'BC' Version: arXiv 2607.17227v2, updated 2026-09-17 (v1 posted 2026-07-19) Retrieved: 2026-10-11T21:29:34Z	not individually reviewed No individual claim review recorded independent paper Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `attributes.comparison.protocol_id` Source artifact SHA-256: `8137338c6146f570a6546f30707d4244baca9dab848b32c51539665a5ba539da` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison: split All cells (unsupervised clustering) Context-only references	Harmonised benchmarking of foundation models for single-cell and spatial transcriptomics reveals context-dependent generalisation Original source ↗ Table 2, model 'scGPT-spatial', dataset 'BC' Version: arXiv 2607.17227v2, updated 2026-09-17 (v1 posted 2026-07-19) Retrieved: 2026-10-11T21:29:34Z	not individually reviewed No individual claim review recorded independent paper Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `attributes.comparison.split` Source artifact SHA-256: `8137338c6146f570a6546f30707d4244baca9dab848b32c51539665a5ba539da` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Origin independent_paper Context-only references	Harmonised benchmarking of foundation models for single-cell and spatial transcriptomics reveals context-dependent generalisation Original source ↗ Table 2, model 'scGPT-spatial', dataset 'BC' Version: arXiv 2607.17227v2, updated 2026-09-17 (v1 posted 2026-07-19) Retrieved: 2026-10-11T21:29:34Z	not individually reviewed No individual claim review recorded independent paper Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `attributes.origin` Source artifact SHA-256: `8137338c6146f570a6546f30707d4244baca9dab848b32c51539665a5ba539da` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact

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Sources and history

Release 2026-10-23-5347695500ed · Record review: source checked

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Harmonised benchmarking of foundation models for single-cell and spatial transcriptomics reveals context-dependent generalisation · Original source · arXiv 2607.17227v2, updated 2026-09-17 (v1 posted 2026-07-19)

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Technical metadata and extraction receipts

Stable ID: lit-cells-networks-20261011-chen2026-eval-zs-cluster-bc-scgpt-spatial

areas: single-cell; spatial-omics
contexts: research
origin: independent_paper
protocol: lit-cells-networks-20261011-chen2026-protocol-zs-cluster-bc
version: Primary source as retrieved 2026-10-11
comparison: protocol id: lit-cells-networks-20261011-chen2026-protocol-zs-cluster-bc; dataset version: Not reported; split: All cells (unsupervised clustering); population: Not reported; inputs: Single-cell or spatial expression matrix, aligned to each model's gene vocabulary; adaptation: frozen pretrained embeddings, Leiden clustering with resolution tuned to the number of reference labels, seed 42; metric implementation: Not reported; aggregation: Not reported; budget: Not reported
source locator: Table 2, model 'scGPT-spatial', dataset 'BC'
missing metadata: comparison.aggregation: reason: unreported; comparison.budget: reason: unreported; comparison.dataset version: reason: unreported; comparison.metric implementation: reason: unreported; comparison.population: reason: unreported

Related records

system: scGPT-spatial (zero-shot, Chen et al. 2026)
assessment: Chen et al. 2026 zero-shot cell type and spatial domain clustering, BC
data: BC (Chen et al. 2026)
evaluation: scGPT-spatial BC ARI (Table 2)
evaluation: scGPT-spatial BC NMI (Table 2)
evaluation: scGPT-spatial BC Silhouette (Table 2)

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