Sound Design for Vocalizations: Quality in the Woods, Consistency in the Fields
Bibliographic record
Abstract
Abstract The acoustic adaptation hypothesis (AAH) predicts that vocalizations intended for unambiguous long range communication should possess amplitude modulation (AM) characteristics such that the temporal patterning of amplitude degrades less than alternative patterns during transmission through native habitat. The specific predictions are that open habitat signals should be structured as rapid AM trills, whereas closed habitat signals should be structured as low-rate AM tonal whistles. To investigate the benefit of trill- and whistle-structured signals in open and closed habitats, respectively, a high and low carrier frequency set of four synthetic signals which ranged from rapid AM trills to low rate AM whistles were transmitted 3 hours after sunrise through five different habitat types ranging from closed mature forest to open grassland. Results indicate that, on average, whistles degrade less than trills in both habitats. Trills benefit in open habitats through their tendency to be received with a more consistent quality than whistles. Such differences in transmission consistency among AM patterns are not found in closed habitats. While not degrading less on average, lower frequency signals are received with a more consistent quality than are higher frequency signals of the same AM structure, in both open and closed habitats.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".