Vulnerability to Fishing and Life History Traits Correlate with the Load of Deleterious Mutations in Teleosts
Bibliographic record
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 data set of 76 species of teleostean fishes, we show that species with life history traits associated with vulnerability to fishing have an increased rate of deleterious mutation accumulation (measured via dN/dS, i.e., nonsynonymous over synonymous substitution rate). Our results, focusing on a large clade of aquatic species, generalize previous patterns found so far in few clades of terrestrial vertebrates. These results also show that vulnerable species to fishing inherently accumulate more deleterious substitutions than nonthreatened ones, which illustrates the potential links among population genetics, ecology, and fishing policies to prevent species extinction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".