Vulnerability and life-history traits correlate with the load of deleterious mutations in fish
Bibliographic record
Abstract
Abstract Understanding why some species accumulate more deleterious substitutions than others is an important question relevant in evolutionary biology and conservation sciences. Previous studies conducted in terrestrial taxa suggest that life history traits correlate with the efficiency of purifying selection and accumulation of deleterious mutations. Using a large genome dataset of 76 species of fishes, we show that the rate of deleterious mutation accumulation (measured via dN/dS, i.e. non-synonymous over synonymous substitution rate) is associated to the vulnerability, the life-history strategies, and the latitude of species. Our results, focusing on a large clade of aquatic species, generalizes previous patterns found so far in few clades of terrestrial vertebrates. These results also suggest that vulnerable species accumulate more deleterious substitutions than non-threatened ones, which give insights in how life-history traits, populations sizes and genetic risk of extinction can be tightly interconnected.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".