Salience of Caller Identity in Rhesus Monkey (Macaca mulatta) Coos and Screams: Perceptual Experiments With Human (Homo sapiens) Listeners.
Bibliographic record
Abstract
Recent evidence from acoustic analysis and playback experiments indicates that adult female rhesus monkey (Macaca mulatta) coos are individually distinctive but their screams are not. In this study, the authors compared discrimination of individual identity in these sounds by naive human listeners who judged whether 2 sounds had been produced by the same monkey or 2 monkeys. Each of 3 experiments using this same-different design showed significantly better discrimination of vocalizer identity from coos than from screams. Experiment 1 demonstrated the basic finding. Experiment 2 also tested the effect of non-identity-related scream variation, and Experiment 3 added a comparison with human vowel sounds. Outcomes suggest that acoustic structural differences in coos and screams influence salience of caller-identity cues, with significant implications for understanding the functions of these calls.
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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 | 0.003 |
| 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 | 0.001 |
| 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".