Dive shapes reveal temporal changes in the foraging behaviour of different age and sex classes of harbour seals (<i>Phoca vitulina</i>)
Bibliographic record
Abstract
Classifying dives into two-dimensional shapes based on time and depth is an attempt to extract additional information about the behaviour of aquatic air-breathing predators. In some species, there is considerable circumstantial evidence that different dive shapes represent different behaviours. However, few studies have provided direct evidence of the relationship between dive shape and function. We classified over 283 000 dives of adults (31 males and 45 females) and suckling (13) and recently weaned (15) harbour seal (Phoca vitulina) pups into seven shapes using supervised discriminant function analysis. Changes in the percentage of U-shaped dives over time within adults and weaned pups were associated with changes in food intake derived from water-flux studies on subsets of the same individuals. The changes in the percentage of U-shaped dives were accompanied by roughly reciprocal changes in V-shaped dives, whereas there was little change in other dive shapes, indicating that V-shaped dives are not generally exhibited during foraging. Video of adult males (from an animal-borne video system) also showed that there was a strong but not exclusive association between foraging and U-shaped dives. Our results indicate that changes in the percentage of U-shaped dives may serve as a reasonable index of changes in foraging behaviour. However, behaviours of suckling pups and adult males during the breeding season cannot be easily inferred from dive shape alone.
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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 | 0.000 |
| 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) | 0.001 | 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".