La fauna acompañante del langostino patagónico (Pleoticus muelleri) en el Golfo San Jorge y adyacencias: análisis de alternativas de manejo.
Bibliographic record
Abstract
En el presente trabajo se evalúan distintas alternativas de manejo de la fauna acompañante de la pesca industrial del langostino patagónico (Pleoticus muelleri) en el Mar Argentino. Se analiza, además, la relación entre la captura por unidad de esfuerzo de langostino y la de merluza (Merluccius hubbsi) sobre la base de datos de observadores a bordo obtenidos en 189 mareas de buques tangoneros. Se concluye que ambas variables son independientes. Finalmente, se presentan recomendaciones de manejo. In this paper different management alternatives of Patagonian red shrimp (Pleoticus muelleri) in Argentine Sea industrial fishing bycatch are evaluated. Besides, the relationship between red shrimp and hake (Merluccius hubbsi) catch per unit effort is analyzed on the basis of data gathered by observers on board in 189 outrigger trips. It is concluded that both variables are independent. Finally, management recommendations are presented.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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; both teacher heads agree on what is shown here.
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".