Genetic population structure in Greenland halibut (<i>Reinhardtius hippoglossoides</i>) and its relevance to fishery management
Bibliographic record
Abstract
Exploited marine resources can be managed more effectively when accurate information on geographic population structure is available. Genetic markers offer a powerful tool for fisheries management, because they reveal biologically sound management units. Single nucleotide polymorphisms (SNPs) markers derived from restriction-site associated DNA sequencing (RAD-seq) were developed and used to investigate the stock structure of Greenland halibut (Reinhardtius hippoglossoides). A total of 96 SNPs were analyzed from 384 individuals and eight locations across the Atlantic. Our results suggest a subdivision of Greenland halibut into two populations, an eastern Atlantic population and a western Atlantic population, with a proposed border across the Denmark Strait. In general, Greenland halibut display weak but significant population structure (overall FST = 0.003; p < 0.001), which can be explained by connectivity among populations owing to the migratory behavior or egg and larval drift.
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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 | 0.001 |
| 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".