Stock-of-origin catch estimation of Atlantic bluefin tuna (<i>Thunnus thynnus</i>) based on observed spatial distributions
Bibliographic record
Abstract
Atlantic bluefin tuna (Thunnus thynnus) are a large, highly migratory fish distributed throughout the North Atlantic Ocean and adjacent seas currently managed as two discrete stocks: western and eastern. Both stocks forage in the North Atlantic, and a high degree of intermixing occurs, which combined with limited single-stock survey data makes it difficult to assess the abundance and status of individual populations. In this study, we used movement patterns from a multidecadal tagging dataset to create monthly distribution maps for these two major stocks. We then used these maps to separate the overall catch records into stock-specific catch (catch per unit effort, CPUE) time series. We identified an increase in the past two decades in the proportion of catch estimated to come from the eastern stock, attributable to a decrease in CPUE in regions dominated by the western stock, relative to other regions. The stock-specific catch series can be used to improve the accuracy of stock assessments and inform spatial management.
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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 | 0.001 | 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 | 0.000 | 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) | 0.000 | 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".