Electronic tags reveal high migratory diversity within the largest Atlantic halibut (<i>Hippoglossus hippoglossus</i>) stock
Bibliographic record
Abstract
Growing evidence suggests that complex spatial structure occurs within the Scotian Shelf and southern Grand Banks (SSGB) Atlantic halibut stock, yet large knowledge gaps remain about diversity of migratory and spawning behaviors. Here, 71 pop-up satellite archival tags were deployed on large Atlantic halibut (FL: 87–166 cm) between 2012 and 2020. Migration tracks were successfully reconstructed for 43 fish using a hidden Markov geolocation model, and temperature and depth time series were available for an additional nine fish (total n = 52). Five migratory behavior categories were identified: shelf residency, slope residency, shelf-channel migration, shelf-slope migration, and dispersal. High-resolution data for four of 20 physically recovered tags provided evidence of putative spawning behavior in deep channels on the continental shelf and along the continental slope between January and February. Additionally, four halibut displayed previously undocumented periods of sustained, oscillatory vertical movements along the continental slope between November and February. The high migratory diversity observed in this study provides support for the existence of multiple resident and migratory contingents in the SSGB stock in the apparent absence of significant genetic structure.
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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".