Additional file 2 of Comprehensive transcriptional variability analysis reveals gene networks regulating seed oil content of Brassica napus
Bibliographic record
Abstract
Additional file 2: Table S1. Genome-wide eQTLs identified at 20 DAF. Table S2. Genome-wide eQTLs identified at 40 DAF. Table S3. Genome-wide eGene-eQTLs identified at 20 DAF. Table S4. Genome-wide eGene-eQTLs identified at 40 DAF. Table S5. Results of GO enrichment analysis of specifically identified eGenes at 20 DAF. Table S6. Results of GO enrichment analysis of specifically identified eGenes at 40 DAF. Table S7. Summary of ATAC-Seq data. Table S8. List of homoeologous genes among subgenomes. Table S9. List of homoeologous genes on gene expression trend and regulation at 20 DAF. Table S10. List of homoeologous genes on gene expression trend and regulation at 40 DAF. Table S11. The information of hotspots at 20 DAF. Table S12. The information of hotspots at 40 DAF. Table S13. The list of TWAS significant genes of SOC and SGC at 20 DAF. Table S14. The list of TWAS significant genes of SOC and SGC at 40 DAF. Table S15. Enrichment analysis of eQTL hotspot regulatory genes in TWAS significant genes of SOC at 20 DAF. Table S16. Enrichment analysis of eQTL hotspot regulatory genes in TWAS significant genes of SOC at 40 DAF. Table S17. The results of Tomtom analysis of key sequences identified by Basenji module. Table S18. Primers for gene cloning and PCR confirmation.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.750 | 0.154 |
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".