Additional file 1 of Monocyte, neutrophil, and whole blood transcriptome dynamics following ischemic stroke
Bibliographic record
Abstract
Additional file 1: Table S1. Differentially expressed genes (DEGs) significant to time point (TP) p-value < 0.02 on the contrasts IS TP vs. VRFC (TP0). Table S2. Enriched canonical pathways overrepresented in all time points (TP) (Fisher's p-value < 0.05). Table S3. Predicted upstream regulators in all time points (TP) (Fishers' p-value < 0.05). Table S4. Differentially expressed genes (DEGs) distributed per GEDI map tile based on Pearson's correlation of gene expression values. Table S5. Differentially expressed genes (DEGs) distributed per SOM profile based on Euclidean distance. Table S6. GO terms for biological processes enriched in the SOM profiles from Fig. 6. Table S7. Subject demographics and relevant clinical characteristics in the time bins analyzed after regrouping per IS etiology. Table S8. Differentially expressed genes (DEGs) significant to time point (TP) p-value < 0.02 on the contrasts IS TP-IS etiology vs. VRFC (TP0). Table S9. DEGs distributed per SOM profile in all IS etiologies, based on Euclidean distance. Table S10. GO terms for biological processes enriched in the SOM profiles from Fig. 9, for all IS etiologies. Table S11. Genes in WGCNA modules associated time (h). Table S12. Hub genes in the modules significant to time (h). Table S13. HumanBase functional clustering of hub genes from time-associated modules and their corresponding gene ontology terms. Table S14. Correlation between NIHSS at admission and expression of time-associated hub genes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.787 | 0.119 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".