Bibliographic record
Abstract
Abstract When animals live in cohesive groups they need to make consensus decisions about movements. As a very large‐scale example of communal movement, nomadic female sperm whales ( Physeter macrocephalus ) travel about 50 km per day as coherent groups of 10–50 animals spread over several km of ocean. From 543 h of data during which 3,873 headings of small clusters of whales or individual whales were recorded, I quantified the heading behavior of groups foraging off the Galápagos Islands. The groups made both sudden and gradual turns. Using piecewise regression models, I estimate that sudden and gradual turns in heading both occurred at rates of 0.10/h. The mean change in heading was 69° for sudden turns and 84° for gradual turns. The mean duration of gradual turns was 1.3 h, so turns were often slow. Using the recorded headings within 30 min of each of 1,798 focal headings, a regression of heading on time gave a mean rate of turn of the group and error of each focal heading about the mean heading. Absolute heading errors increased with absolute turn rate ( r S = 0.241; P = 0.0000), so turns were often messy. Thus sperm whales often make slow and messy—likely democratic—consensus decisions when groups change heading.
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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 | 0.004 |
| 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 | 0.001 |
| 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 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".