Additional file 1 of Selection on the promoter regions plays an important role in complex traits during duck domestication
Bibliographic record
Abstract
Additional file 1. Table S1. Summary of multi-omics sequencing data during duck domestication. Table S2. Variation annotation detected in mallard and Pekin duck populations. Table S3. Genes that are located in the top 5% of selected regions. Table S4. The effect and number of variations in the gene body of selected genes in the mallard and Pekin duck population. Table S5. Selection and regulation characteristics of upstream selected genes. Table S6. Summary of ATAC-Seq data mapped to the mallard reference genome. Table S7. Summary of Hi-C data mapped to the mallard reference genome. Table S8. Genes located near the differential TAD boundaries between mallard and Pekin duck. Table S9. Different expression signatures of genes with selected promoters with potential regulatory regions in upstream of breast muscle, liver, and fat tissues. Table S10. The traits affected by genes with selected promoters with functions related to selected traits in other studies. Table S11. Quantitative Results of Medium and Long Chain Fatty Acids by Gas Mass Spectrometry. Table S12. Specific differentially expressed genes during adipocyte differentiation induced by overexpression of ELOVL3 compared with wild type. Table S13. Sequence information relating to primers designed in this study. Table S14. Standard curve of Medium and Long Chain Fatty Acids by Gas Mass Spectrometry.
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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 | 0.012 |
| 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 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.828 | 0.170 |
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".