Additional file 1 of Gene gain and loss from the Asian corn borer W chromosome
Bibliographic record
Abstract
Additional file 1: Figure S1. Genome survey of Ostrinia furnacalis using k-mer analysis. Figure S2. The genome-wide Hi-C interaction maps of 32 chromosomes in Ostrinia furnacalis. The map indicates that intrachromosome interactions were strong while interchromosome interactions were weak. The shading gradient represents the chromosome interactions. Figure S3. Synteny analysis between Ostrinia furnacalis and Spodoptera litura chromosomes. Chromosomes of Ostrinia furnacalis are shown in the left, number 3 represent the W chr and 1 represents the Z chr. The chromosomes of Spodoptera litura are shown in the right. Figure S4. Annotation and evaluation of protein-coding genes. a. Genes annotated via ab initio, homology-based and RNA-seq methods. b-e. Comparison of Ostrinia furnacalis gene features with other lepidopteran genomes. Figure S5. The number of repeat sequences in W chromosome (LG3). Figure S6. The number (a-b), density (c-d) and proportion (e-f) of repeat sequence in all chromosomes (LG1-LG32). Table S1. Chromosome-level assembled Lepidoptera genomes. Table S2. Assessments of assembled genome. Table S3. Genomic annotation of Ostrinia furnacalis. Table S4. Copy number for W and autosomal/Z chromosome paralogs. Table S5. Statistics of genomic sequencing data of Ostrinia furnacalis by PacBio Sequel II. Table S6. Statistics of genomic sequencing data of Ostrinia furnacalis by Hi-C. Table S7. Statistics of genomic resequencing data of female and male pupae and transcriptome sequencing of female gonads and a mixed sample. Table S8. The download address of insect species protein sequences used for comparative genomics analysis and phylogenetic reconstruction.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 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) | 0.823 | 0.160 |
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".