Love the one you’re with: genomic evidence of panmixia in the sablefish (<i>Anoplopoma fimbria</i>)
Bibliographic record
Abstract
Understanding the genetic structure of a fishery may help delineate stocks and is directly applicable to resource management. To date, studies have not found clear population genetic structure across the range of the sablefish (Anoplopoma fimbria), yet significant biological differences are recognized. Here we use restriction site-associated DNA sequencing to develop thousands of single nucleotide polymorphisms (SNPs) throughout the sablefish genome and assess population genetic structure and examine the genome for SNPs under natural selection. Our study was unable to target spawning groups, having the potential to bias analyses that require a priori hypotheses of population structure. Low and insignificant levels of differentiation (FST = 0.0002) were observed among survey areas, and analyses of population structure suggested a single population. Only two SNPs were significantly associated with environmental variables. These results are likely due to considerable population mixing and suggest a single panmictic group of sablefish off the west coast of the United States and Alaska that is likely a consequence of a complex juvenile life history and long range movements as adults.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".