Population structure discovered in juveniles of Greenland halibut (<i>Reinhardtius hippoglossoides</i>Walbaum, 1792)
Bibliographic record
Abstract
Abstract Understanding the genetic differentiation among populations of most marine fish requires investigating the differences among spawning grounds. However, this can be challenging as spawning grounds for some species are not well known, or spawning fish are difficult to collect. An alternative is to collect juvenile fish in nursery habitats closely associated with potential spawning grounds. Greenland halibut is a deep-dwelling, commercially important species with at least two identified major offshore spawning grounds in the North Atlantic and weak genetic differentiation across the Atlantic. In this study, we sampled juveniles from three sites representing the Davis Strait spawning area in the northwest Atlantic and one site in the northeast Atlantic representing the primary spawning area along the western slope of the Barents Sea. We applied genotype by sequencing and discovered 90 genetic markers that could be used to assess genetic differentiation among the four sites. The northeast and northwest Atlantic showed major genetic differentiation, supporting the existence of the two primary spawning clusters. Additionally, we found genetic differentiation between the three northwest Atlantic samples implying the existence of more than one spawning area in the northwest.
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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 | 0.000 |
| 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) | 0.001 | 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".