Autopolyploidy Genome Duplication Preserves Other Ancient Genome Duplications In Atlantic Salmon (Salmo Salar) Supplementary Datasets
Bibliographic record
Abstract
For various species, alignments were found between a protein database (produced from Zebrafish) and the sequenced genome of that species. Using Perl scripts and the alignments, gene models were identified in the various species based on the protein sequences. The gene models, for the various species, can be found in the .gff3 files. Some of the .gff3 files have had ribosomal proteins removed. Homeologous regions were then identified using Perl scripts and can be found in .gff3 files as well. They have Homeologous_Regions.gff3 in their title. Homeologous genes in these regions were counted (named XX_XX_Homeologous_Regions.txt), and compared to all of the genes (not just homeologous genes) in these regions (named Gene_Count_Homeolgous_XX_XX_XX.txt) to find the density. Homeologous gene sequences were compared to each other to identify the Ps values between them using a program called SNAP (Files with _Homeologous_region_analysis_version_1.2.txt at the end). The analyses of these files are summarized in "Pn_Ps_Values_Vertebrate_Homeologous_Regions.ods." The synteny between species can be found in the files with .seg extensions (These can be opened in IGV). A comparison between the gene density and Ps value for each homeologous region can be found in the file, "Gene_Density_Compared_to_Ps_Values.ods." Included is an extended readme file and Perl scripts (.pl extension) in a compressed file (Final_Scripts.tar.gz).
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.161 | 0.040 |
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".