Additional file 2 of Selection on the promoter regions plays an important role in complex traits during duck domestication
Bibliographic record
Abstract
Additional file 2: Fig. S1 The characteristics of FST and nucleotide polymorphism distribution of selected genes in MapleLeaf duck, ShaoXing duck, GaoYou duck, and JinDing duck. Fig. S2 Simulation of fixation index between Pekin duck and mallard populations during duck domestication. Fig. S3 The ATAC-seq signal enrichment around the transcription start sites (TSSs) for 10 representative samples. Fig. S4 The distribution of the distance from peaks that were annotated to promoter region to the gene TSS. Fig. S5 Comparison of breast muscle tissue and myofibers between mallard and Pekin duck during the rapid developmental stage after hatching. Fig. S6 The number of differentially expressed genes during dynamic development of breast muscle, liver, and fat tissue in mallard and Pekin duck. Fig. S7 The expression profile of BIN3 in 16 tissues of mallard and Pekin duck. Fig. S8 The expression profile of ELOVL3 in 16 tissues of mallard and Pekin duck. Fig. S9 Selective sweep regions arising from domestication found around the ELOVL3 region on chromosome 7. Fig. S10 The SNP sites and allelic frequencies of ELOVL3 core promoter region in local duck breeds. Fig. S11 Construction of mutation at site -619 (A
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.856 | 0.180 |
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".