Tracking the fidelity of Atlantic bluefin tuna released in Canadian waters to the Gulf of Mexico spawning grounds
Bibliographic record
Abstract
The objective of this study was to advance the use of pop-up satellite archival tags to track the migrations of Atlantic bluefin tuna (Thunnus thynnus) to their spawning grounds. Deployment of tags occurred in the Gulf of St. Lawrence, Canada, during fall months from 2007 to 2013. Pop-up satellite archival tags (n = 135) were attached to 125 Atlantic bluefin tuna (curved fork length (CFL) = 268 ± 20 cm (mean ± SD)) with the objective of keeping tags on until visitation to a spawning area or longer. A dataset of 18 800 days was acquired, which included 5800 days of time-series data from 19 recovered satellite tags. Many Atlantic bluefin tuna visited the Gulf of Mexico spawning grounds (74%), the mean size of which was 275 ± 14 cm (CFL ± SD, n = 49), with a measured CFL of 243 to 302 cm. These fish had a mean entry date into the Gulf of Mexico of 14 January ± 42 days (SD). The mean residency period for fish that had tracks with entrance and exit from the Gulf of Mexico was 123 ± 49 days (SD) (n = 22). Atlantic bluefin tuna that moved into the Gulf of Mexico during the spawning season remained west of the 45°W meridian for the duration of the track. Electronic tagging datasets from two fish were obtained before, during, and after the Deepwater Horizon oil spill. Both fish utilized habitat in the vicinity of the Macondo Well on 20 April 2010 when the Deepwater Horizon oil drilling rig accident occurred. Spawning hotspots are identified in the Gulf of Mexico using kernel density analyses and compared with the newly established closed areas.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| 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".