Oil sardine (<i>Sardinella longiceps</i>) off the Malabar Coast: density dependence and environmental effects
Bibliographic record
Abstract
Abstract Marine fish stocks are known for extensive variation in landings, with temporal fluctuations attributable to density‐dependent as well as environmental effects. In this paper we analysed a 44‐yr time‐series of oil sardine Sardinella longiceps landings from the Arabian Sea off the Malabar Coast of India. Density dependence was detected in the landings of oil sardine, reinforcing the potential for sustainable yields. Significant environmental factors (precipitation and sea level reflecting the strength of upwelling) during the monsoon period (June–August) are hypothesized to affect the dynamics of landings by influencing spawning and recruitment success. Together, density dependence and environmental variability during the monsoon explained 80% of the among‐years variance in landings. Our results have important consequences for understanding catch variability and are potentially useful for facilitating management of this commercially important fishery.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".