Sounds Scary? Lack of Habituation following the Presentation of Novel Sounds
Bibliographic record
Abstract
BACKGROUND: Animals typically show less habituation to biologically meaningful sounds than to novel signals. We might therefore expect that acoustic deterrents should be based on natural sounds. METHODOLOGY: We investigated responses by western grey kangaroos (Macropus fulignosus) towards playback of natural sounds (alarm foot stomps and Australian raven (Corvus coronoides) calls) and artificial sounds (faux snake hiss and bull whip crack). We then increased rate of presentation to examine whether animals would habituate. Finally, we varied frequency of playback to investigate optimal rates of delivery. PRINCIPAL FINDINGS: Nine behaviors clustered into five Principal Components. PC factors 1 and 2 (animals alert or looking, or hopping and moving out of area) accounted for 36% of variance. PC factor 3 (eating cessation, taking flight, movement out of area) accounted for 13% of variance. Factors 4 and 5 (relaxing, grooming and walking; 12 and 11% of variation, respectively) discontinued upon playback. The whip crack was most evocative; eating was reduced from 75% of time spent prior to playback to 6% following playback (post alarm stomp: 32%, raven call: 49%, hiss: 75%). Additionally, 24% of individuals took flight and moved out of area (50 m radius) in response to the whip crack (foot stomp: 0%, raven call: 8% and 4%, hiss: 6%). Increasing rate of presentation (12x/min ×2 min) caused 71% of animals to move out of the area. CONCLUSIONS/SIGNIFICANCE: The bull whip crack, an artificial sound, was as effective as the alarm stomp at eliciting aversive behaviors. Kangaroos did not fully habituate despite hearing the signal up to 20x/min. Highest rates of playback did not elicit the greatest responses, suggesting that 'more is not always better'. Ultimately, by utilizing both artificial and biological sounds, predictability may be masked or offset, so that habituation is delayed and more effective deterrents may be produced.
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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 | 0.002 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".