Consumption of juvenile herring (<i>Clupea harengus</i>) by cod (<i>Gadus morhua</i>) in the Barents Sea: a new approach to estimating consumption in piscivorous fish
Bibliographic record
Abstract
Consumption of different age groups of juvenile, Norwegian, spring-spawning herring (Clupea harengus) by northeast Arctic cod (Gadus morhua) in the Barents Sea in 19921997 is estimated using cod stomach content data. We present a new approach to the problem of estimating consumption by fish. The new method is based on the estimation of digestion time for single prey items based on the difference between fresh weight at ingestion and weight in the stomach at time of sampling. Estimation is based on a gastric evacuation model for cod and area-specific sea temperatures. This is used to estimate the time (tmax) it takes for a prey to become digested to a stage where length is no longer measurable. Predation rate is then estimated for all prey with digestion time ≤tmax as number of prey eaten in the time range defined by tmax. This rate is combined with estimates of the proportion of the cod stock consuming the prey and area-specific abundance of cod, giving consumption of herring on a seasonal and yearly basis. The consumption estimates differ from those obtained using current methods. Predation mortality of herring is estimated directly from the consumption estimates by combining them with acoustic herring abundance data.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".