Length-length, Length–weight, and Weight-weight Relationships of Yellowfin (Thunnus Albacares) and Bigeye (Thunnus Obesus) Tuna Collected From the Commercial Handlines Fisheries in the South China Sea
Bibliographic record
Abstract
Abstract Tuna fisheries have become the most important contributor to the coastal central provinces of Vietnam since it was introduced in early 1990s. However, developing effective management guidelines for yellowfin ( Thunnus albacares ) and bigeye ( Thunnus obesus ) tuna, the main target species for longline and handline fisheries, is difficult because there is no information on its growth characteristics. In particular, length-length, length–weight, and weight-weight relationships, the important components of fisheries production models, do not exist for those species. This study first provided those relationship equations and represented an improvement in the knowledge of these species in its distribution range with maximum sizes updated.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".