VOCAL INDIVIDUALITY IN MOTHER AND PUP SOUTH AMERICAN FUR SEALS, <i>ARCTOCEPHALUS AUSTRALIS</i>
Bibliographic record
Abstract
Abstract South American fur seals breeding in Peru are subjected to levels of maternal aggression, and subsequent pup mortality, that are higher than has been reported for any other otariid species. For mothers and pups to maintain contact with each other, a mutual recognition system should exist to facilitate reunion and avoid misdirection of maternal effort. We recorded vocalizations of mothers and pups at Punta San Juan, Peru, during the 1994 and 1995 breeding seasons. Sixteen acoustic variables were measured from a total of 560 calls from 15 mothers and 13 pups. Multivariate analysis showed that calls were variable in several acoustic dimensions. While calls of both mothers and pups showed low variability within and high variability among individuals, mothers' calls were more individualistic. On average, discriminant‐function analysis correctly assigned 60% of pup calls and 70% of mother calls to the individual that produced them. Characteristics of the fundamental frequency were most important for distinguishing among mothers, while pup calls, which typically contained less harmonic structure, could be differentiated by formant‐like frequency ranges. Thus, calls of mother and pup South American fur seals appear to exhibit sufficient stereotypy to allow for recognition and discrimination among individuals.
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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 | 0.000 | 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) | 0.001 | 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".