Seasonal dispersion of Pacific halibut (Hippoglossus stenolepis) summering off British Columbia and the US Pacific Northwest evaluated via satellite archival tagging
Bibliographic record
Abstract
Fisheries for eastern Pacific halibut ( Hippoglossus stenolepis ) occur over a 9-month season that is closed in winter to protect spawners. The industry has requested season extension, but conventional tag data suggest that 67% of Canada’s fishable biomass may comprise Alaskan spawning stock vulnerable to out-of-area interception. Seventy-eight halibut were tagged during summer in Canada and the US Pacific Northwest (USPNW) with archival tags programmed to report via satellite on 1 February, 15 February, and 1 March. Fifty-seven tags (44 Canadian and 13 USPNW) escaped recapture and reported on or near their scheduled reporting dates. Only 7% out-of-area dispersion was observed for Canadian-tagged halibut; light-based geolocations suggested that an additional 4% may have emigrated prior to February and then returned. Halibut that emigrated were located north of their tagging location. From the USPNW, 46% dispersion was observed. Eighty-nine percent of the tagged halibut displayed depth profiles consistent with migration to offshore spawning areas during the winter, and the majority (78%) were located on the continental slope (>200 m) immediately prior to tag reporting, suggesting locations on or near spawning grounds. There was no detectable difference in dispersion by date, but the mean central position of Canadian-tagged halibut shifted progressively farther southeast over time.
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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 | 0.001 |
| 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 | 0.001 | 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".