Evidence of bluefin tuna (<i>Thunnus thynnus</i>) spawning in the Slope Sea region of the Northwest Atlantic from electronic tags
Bibliographic record
Abstract
Abstract Atlantic bluefin tuna (ABT) are large, wide-ranging pelagic predators, which typically migrate between foraging regions in the North Atlantic and two principal spawning regions, the Gulf of Mexico and the Mediterranean Sea. A new spawning area has been described in the Slope Sea (SS) region off New England; however, the relationship between ABT that spawn in the SS and ABT using the principal spawning regions remains poorly understood. We used electronic tags to examine the location, temperature, and diving behaviour of ABT in the SS, and identified 24 individuals that were present during the spawning season (June–August) with tag data showing temperatures and behaviour consistent with spawning ABT. In general, the SS spawners had similar spatial ranges to Mediterranean-spawning ABT; however, some individuals displayed distinct behaviours that were identified first in the Gulf of Mexico spawners. Using monthly spatial distributions, we estimated that the SS spawners have high exposure to fishing pressure relative to other ABT and may represent a disproportionate share of the West Atlantic catch. This analysis provides the first description of the behaviour of ABT frequenting this spawning ground, creating a foundation for integrating this region into multi-stock management and, potentially, conserving an important source of genetic diversity.
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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 | 0.000 | 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".