High offshore migration rates and multiple movement phenologies of acoustically tagged Greenland halibut (<i>Reinhardtius hippoglossoides</i>) in the Eastern Canadian Arctic
Bibliographic record
Abstract
Understanding spatiotemporal movements of targeted species is fundamental to fisheries management. In the Arctic, Greenland halibut ( Reinhardtius hippoglossoides) fisheries are managed as separate stocks, and potential future fisheries growth requires improved understanding of broadscale movements and migration phenologies. We tagged Greenland halibut in the community fishery of Pond Inlet, Nunavut, Canada with acoustic transmitters to assess inshore and offshore movements over 4 years. Fish tagged in summer showed longer residency in Pond Inlet (54 ± 27 days) compared to offshore (2 ± 3 days) southern Baffin Bay/northern Davis Strait. Winter-tagged fish also showed high residency in Pond Inlet (92 ± 47 days) and minimal overlap with summer-tagged fish (December–April vs. June–November). Offshore migrations were detected in the majority of summer-tagged (70%) and winter-tagged fish (83%). Few summer-tagged fish returned to Pond Inlet in subsequent years, while most winter-tagged fish returned to Pond Inlet. These complex movements indicate Greenland halibut as a highly migratory species, which should be considered when developing management policies for both offshore and inshore fisheries.
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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 | 0.001 | 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".