Additional file 10 of Constructing a novel mitochondrial-related gene signature for evaluating the tumor immune microenvironment and predicting survival in stomach adenocarcinoma
Bibliographic record
Abstract
Additional file 10: Tables S1–S14. Table S1. The list of mitochondrial-related genes. Table S2. The list of carcinoma associated fibroblast up signatures (n=24). Table S3. The list of carcinoma associated fibroblast down signatures (n=24). Table S4. The list of ECM and Collagen signatures (n=225). Table S5. The list of matrisome signatures (1026). Table S6. The primer sequences. Table S7. The list of all DEGs in tumor and normal groups (n=2381). Table S8. The list of protein-coding DEGs in tumor and normal groups (n=2145). Table S9. The list of mitochondrial-related DEGs (n=183). Table S10. GO terms in tumor and normal groups. Table S11. KEGG terms in tumor and normal groups. Table 12. The list of DEGs in high and low risk groups (n=298). Table S13. GO terms in high and low risk groups. Table S14. KEGG terms in high and low risk groups .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.439 | 0.076 |
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".