The squeaking vocalization of grey wolves (Canis lupus): individuality in a close-range affiliative mammalian vocalisation
Bibliographic record
Abstract
Abstract Wolves (Canis lupus) frequently use the close-range squeaking vocalization, a soft, multi-unit, high-pitched tonal vocalisation. We examined the social and movement contexts of the occurrence and acoustic characteristics of squeaking from videotapes of pack-reared, pack-living captive wolves living in semi-natural conditions at the Canadian Centre for Wolf Research over a three-year period. We only examined squeaking vocalisations for which the sender and potential receiver(s) could be determined. Wolves squeaked in many contexts, especially when approaching other wolves in prosocial and food contexts. Some wolves squeaked more than others. Acoustically, squeaking vocalisations were individually identifiable, primarily through frequency characteristics. Contextual use suggests that squeaking conveys the friendly motivation of an approaching wolf and in aggressive situations, a motivation to defuse or decrease aggression. This close-range vocalisation may play an important role in controlling and coordinating social interactions within the pack.
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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".