Diel variation of stomach contents of North Sea cod (<i>Gadus morhua</i>) during a 24-h fishing survey: an analysis using generalized additive models
Bibliographic record
Abstract
Results show that the weight of cod (Gadus morhua) stomach contents sampled in the North Sea varies significantly within 24 h. To determine whether feeding varied with time, over 1100 cod stomachs were collected around the clock between 7 and 18 May 1984 in two areas in the central North Sea thought to be representative for feeding studies. Here we investigate temporal feeding patterns based on the analysis of stomach-content data, using generalized additive models (GAMs). Results show significant variation of content weight and indicate morning and evening peaks. The relative peak importance differed between and within areas. We propose that differences are due to diet composition, namely, prey size and diel availability. Cod fed primarily on molluscs, mainly ocean quahog (Cyprina islandica), crustaceans, sandeels (Ammodytes spp.), haddock (Melanogrammus aeglefinus), herring (Clupea harrengus), and several flatfish species. In one area, the diet was dominated by fish, relatively large prey that perform diel vertical migration, and in the other by invertebrates, smaller prey that are digested faster. The diel pattern was more pronounced where invertebrate prey were dominant. Generalisation of results and implications for predation-mortality estimates based on data from the North Sea Stomach Content Database, used to implement multispecies models in the region, are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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".