Quantifying genetic differentiation and population assignment between two contingents of Atlantic mackerel (<i>Scomber scombrus</i>) in the Northwest Atlantic
Bibliographic record
Abstract
In the Northwest Atlantic (NWA), the Atlantic mackerel ( Scomber scombrus) has a northern and a southern contingent, which spawn in Canada and the United States (U.S.), respectively. Both contingents mix mostly along the U.S. shelf during overwintering. The discrimination of individuals from each contingent in fisheries could improve the management of this depleted species in both countries. Here, we used genome-wide markers (>10 000 single nucleotide polymorphisms (SNPs)) to assess genomic differences between mackerel of both contingents, and possibly infer the proportions of each contingent in NWA management units. Small but significant genetic differentiation was observed between the northern and southern contingents ( FST = 0.0010). Genetic assignments to reference samples from the two contingents were performed with predictive accuracy > 85%. Fish from both contingents were present along the U.S. shelf during late winter and early spring but also, without prior evidence of this, likely in Canadian waters from late spring to fall. Genetic assignments could be used as a stock discrimination tool so that fishery removals can be effectively determined and managed on a contingent level.
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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 | 0.000 |
| 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 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".