result · source checked
0.734 F1-Score
scGPT · F1-Score · M.S. single-cell dataset
- Tested model
- scGPT
- Task or benchmark
- Cell-type identification
- Dataset
- M.S. single-cell dataset
- Procedure
- Native scLLM cell-type identification as reported in Table 2.
- Evaluation
- scGPT: Cell-type identification
- Evidence
- Independent external evaluation · source checkedParameter-Efficient Fine-Tuning Enhances Adaptation of Single Cell Large Language Model for Cell Type Identification · Table 2, M.S. / scGPT row, F1-Score column
A source-checked result verifies the numerical transcription, not every model or protocol detail. Evaluation metadata: needs review. Source checked does not mean independently reproduced.
Evaluation results
Release 2026-09-16-d74d282221a9 · 1 evaluation · 1 metric row. Different protocols are not a single leaderboard.
| Metric and finding | Coverage and uncertainty | Evidence |
|---|---|---|
| scGPT: Cell-type identification Native scLLM cell-type identification as reported in Table 2. Independent external evaluation · Evaluation metadata: needs review | ||
| 0.734 F1-Score Unit: unitless · Direction: unknown | Uncertainty: not reported in legacy extract Scored: Not reported · Eligible: Not reported | source checkedParameter-Efficient Fine-Tuning Enhances Adaptation of Single Cell Large Language Model for Cell Type Identification · Table 2, M.S. / scGPT row, F1-Score column Source checking is not independent reproduction. |
Sources and history
Release 2026-09-16-d74d282221a9 · Record review: source checked
- Parameter-Efficient Fine-Tuning Enhances Adaptation of Single Cell Large Language Model for Cell Type Identification · Original source · preprint archived 2024-01-30
Technical metadata and extraction receipts
Stable ID: lit-025
- areas
- cells-tissues
- tasks
- Cell-type identification
- printed value
- 0.734
- numeric value
- 0.734
- metric
- F1-Score
- metric direction
- unknown
- unit
- unitless
- uncertainty
- Not reported
- source locator
- Table 2, M.S. / scGPT row, F1-Score column
- review
- method: independent_ai_table_review; reviewer: Codex omics research agent; independent source-table review, not human review; reviewed at: 2026-09-16T10:41:16.530269+00:00; notes: Selected M.S. dataset block, first scGPT/Geneformer occurrences. F1-Score is last column; later dataset blocks deliberately excluded. This verifies the central score at its source location, not every metadata field or an experimental reproduction.; evidence: {"table_xml_id": "T2", "row_cells": ["M.S.", "scGPT", "0.595", "0.777", "0.728", "0.734"], "selected_cell_zero_based": 5, "selected_cell_xml": "<td align=\"center\" valign=\"bottom\" rowspan=\"1\" colspan=\"1\">0.734</td>", "caption": "Performance of cell type identification using native scLLMs and popular tools.Bold value represents the highest score among the methods"}; artifact sha256: 77a4a859010259eadf2187465db6ab385efa4927a5eadb95c1e01991044c283f; retrieval url: https://www.ebi.ac.uk/europepmc/webservices/rest/PMC10862733/fullTextXML
- legacy id
- lit-025
- legacy row
- id: lit-025; paper id: single-cell-peft-2024; domain id: cells-tissues; task: Cell-type identification; model: scGPT; model version: Not reported; dataset: M.S. single-cell dataset; dataset version: Not reported; split: Not reported; metric: F1-Score; value: 0.734; unit: unitless; uncertainty: Not reported; protocol: Native scLLM cell-type identification as reported in Table 2.; source locator: Table 2, M.S. / scGPT row, F1-Score column; source url: https://pmc.ncbi.nlm.nih.gov/articles/PMC10862733/; evaluation origin: independent_paper; reviewed utc: 2026-09-15T23:25:00Z
- missing metadata
- model version: not_reported_in_legacy_extract; dataset version: not_reported_in_legacy_extract; split: not_reported_in_legacy_extract; uncertainty: not_reported_in_legacy_extract
Related records
- evaluation: scGPT: Cell-type identification
- subject: Reported F1-Score for scGPT