Connectivity and natal sources of Greenland halibut in the gulf of St. Lawrence inferred from otolith chemistry
Bibliographic record
Abstract
Recent genomic study on Greenland halibut Reinhardtius hippoglossoides throughout the Northwest Atlantic revealed genetic differentiation between the Gulf of St. Lawrence and the remainder of the Northwest Atlantic. Knowledge of migration and thus connectivity among fish populations is key to understanding the stock dynamics of commercial species and establishing effective management strategies. In this study, we use otolith microchemistry to assess the population structure and define more clearly the potential connectivity of Greenland halibut among Saguenay Fjord, the Estuary, and the Gulf of St. Lawrence (EGSL) and outside this system. Otolith margins and cores were analyzed to determine the elemental fingerprints. The margin elemental fingerprints (Mg, Sr, and Ba) were used to infer spatial differentiation, and quadratic discriminant analysis resulted in an overall reclassification success of fish to their capture site of 59%. The core elemental fingerprints indicated three chemically distinct juvenile sources, suggesting high connectivity in the EGSL supporting the St. Lawrence Estuary as a main nursery. Our results also suggest that one of these three sources has a smaller contribution relative to the other sites.
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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) | 0.001 | 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".