Additional file 1 of Exploring right ovary degeneration in duck and goose embryos by histology and transcriptome dynamics analysis
Bibliographic record
Abstract
Additional file 1: Supplementary Figure S1. Comparison ofthe number of primordial follicles in the left ovary of individuals withdifferent degeneration of the right ovary on the 6th and 12th, 13th days afterposting; Supplementary Figure S2. The top ten Biologicalprocesses, Cellular components, and Molecular function terms enriched by DEGsbetween DE10 vs. DE20 (A), DE20 vs. DP1 (B), GE12 vs. GE22 (C), GE22 vs. GP1(D); Supplementary Figure S3. The top ten KEGG pathways enriched by DEGsbetween DE10 vs. DE20 (A), DE20 vs. DP1 (B), GE12 vs. GE22 (C), GE22 vs. GP1(D); Supplementary Table S1. Overview of sequencing data; Supplementary Table S2. Mapping rate of RNA-Seq data to the goose reference genome; Supplementary Table S3. All DEGs list; Supplementary Table S4. GO and KEGGenrichment analysis results of DEGs. Supplementary Table S5. GO and KEGG enrichment results of duck- and goose-specific DEGs, respectively. Supplementary Table S6. GO and KEGG enrichment results of genes with different profiles in duck. Supplementary Table S7. GO and KEGG enrichment results of geneswith different profiles in goose. Supplementary Table S8. DEGs and theenrichment results of GO and KEGG during the degeneration of chicken rightovary.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.790 | 0.146 |
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".