Trends in population starvation mortality based on a spatiotemporal model of condition: Part 1: A case study of Atlantic cod on the Southern Grand Bank
Bibliographic record
Abstract
Fish condition is often defined as a deviation in the relationship between fish weight and length, indicating if the fish is leaner or fatter than the average. The proportion of a stock in critically poor condition may indicate a component of the total natural mortality rate M, which has been called the starvation mortality rate (i.e., MK ≤ M). The weight-length relationship may vary spatially and temporally (both between and within years). Hence, MK may also vary the same way. We developed a spatiotemporal condition model to derive a spatiotemporal and length-specific index of MK. We aggregated MK across space and months to produce an annual and length-specific MK index for the entire stock, as a potential input to assessment models. We applied the model to survey data for cod on the Southern Grand Bank of Newfoundland. Our results indicated that MK was: 1) higher in the spring than the fall, 2) higher for cod between 55 and 80 cm and cod ≥ 120 cm, and 3) higher during 1991–1993 when the stock declined substantially, but was also high in 2016. We discuss potential drivers of starvation mortality as well as how this information can be included in a stock assessment model to improve fisheries management advice.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".