Additional file 2 of Multi-omics insights into the positive role of strigolactone perception in barley drought response
Bibliographic record
Abstract
Additional file 2: Supplemental Data 1. Table S1a. List of up-regulated genes in the WT_D vs WT_C comparison (log2FC ≥ 1, adjusted P value ≤ 0.01). Table S1b. List of down-regulated genes in the WT_D vs WT_C comparison (log2FC ≤ -1, adjusted P value ≤ 0.01). Table S1c. List of up-regulated genes in the hvd14_D vs hvd14_C comparison (log2FC ≥ 1, adjusted P value ≤ 0.01). Table S1d. List of down-regulated genes in the hvd14_D vs hvd14_C comparison (log2FC ≤ -1, adjusted P value ≤ 0.01). Table S1e. List of genes up-regulated by drought, only in WT (log2FC ≥ 1, adjusted P value ≤ 0.01) - WT Drought Resposne Specific (WT DRS) genes. Table S1f. List of genes down-regulated by drought, only in WT (log2FC ≤ -1, adjusted P value ≤ 0.01) - WT Drought Resposne Specific (WT DRS) genes. Table S1g. List of genes up-regulated by drought, only in hvd14 (log2FC ≥ 1, adjusted P value ≤ 0.01) - hvd14 Drought Resposne Specific (hvd14 DRS) genes. Table S1h. List of genes down-regulated by drought, only in hvd14 (log2FC ≤ -1, adjusted P value ≤ 0.01) - hvd14 Drought Resposne Specific (hvd14 DRS) genes. Table S1i. List of genes up-regulated by drought, in both genotypes: WT and hvd14 (log2FC ≤ -1, adjusted P value ≤ 0.01). Table S1j. List of genes down-regulated by drought, in both genotypes: WT and hvd14 (log2FC ≤ -1, adjusted P value ≤ 0.01).
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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 | 0.009 |
| 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 | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.736 | 0.159 |
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".