Migration patterns and putative spawning habitats of Atlantic halibut (Hippoglossus hippoglossus) in the Gulf of St. Lawrence revealed by geolocation of pop-up satellite archival tags
Bibliographic record
Abstract
Abstract Characterizing migratory behaviours contributes to the sustainable management of marine fishes by resolving stock structure and identifying the timing and locations of events within fish life cycles. The migratory behaviour of Atlantic halibut (Hippoglossus hippoglossus) in the Gulf of St. Lawrence (GSL), Canada was characterized over an annual cycle using pop-up satellite archival tags (n = 15). Daily probability density functions of individual halibut positions were estimated using a geolocation model specifically developed to track demersal fish species in the GSL. Reconstructed migration routes (n = 8) revealed that Atlantic halibut displayed seasonal migrations, moving from deeper offshore waters in the winter to shallower nearshore waters in the summer. Variability in migratory behaviours was observed among individuals tagged at the same location and time. One individual resided year round in the vicinity of the tagging site, three individuals displayed homing behaviour, and four individuals did not return to the tagging site. The identification of presumed spawning rises for two individuals suggested that spawning of Atlantic halibut occurred in the GSL. Although based on a limited number of individuals, these results suggest that Atlantic halibut in the GSL forms a philopatric population, supporting the current separate management of this stock from the adjacent Scotian Shelf and southern Grand Banks stock.
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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) | 0.000 | 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".