DIRECT ESTIMATION OF WITHIN‐GROUP HETEROGENEITY IN PHOTO‐IDENTIFICATION OF SPERM WHALES
Bibliographic record
Abstract
A bstract Heterogeneity in photo‐identification rates among individuals is a potentially serious problem in many studies of cetacean biology, especially the analysis of populations. However, this heterogeneity is usually difficult to identify or measure. Two instances in which closed groups of female and immature sperm whales ( Physeter macrocepbalus ) were tracked and identified using fluke photographs over periods of days off the Galápagos Islands allowed direct examination of heterogeneity in identification rates. A group of nine animals followed in 1999 provided almost no evidence for heterogeneity (permutation test for heterogeneity, P = 0.48), with an estimated coefficient of variation in identification rates of 0.03 (95% CI from 1,000 bootstrap replications: 0.00–0.10). In contrast, the identification rates of a group of 22 animals followed in 1995 seemed to show potentially important differences ( P = 0.058, CV = 0.20, 95% CI = 0.07–0.28). These differences were not related to the internal social structure of the group or to differences in numbers of markings on the flukes, but smaller whales had lower identification rates. Thus, young sperm whales may be underrepresented in photo‐identification studies, but adults within groups seem to have similar identification rates. Situations in which animals are photo‐identified from closed populations of known size are particularly useful for examining heterogeneity. They should be vigorously exploited by those who use photo‐identification to examine population or behavioral biology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".