Overtone-based pitch selection in hermit thrush song: Unexpected convergence with scale construction in human music
Bibliographic record
Abstract
Many human musical scales, including the diatonic major scale prevalent in Western music, are built partially or entirely from intervals (ratios between adjacent frequencies) corresponding to small-integer proportions drawn from the harmonic series. Scientists have long debated the extent to which principles of scale generation in human music are biologically or culturally determined. Data from animal "song" may provide new insights into this discussion. Here, by examining pitch relationships using both a simple linear regression model and a Bayesian generative model, we show that most songs of the hermit thrush (Catharus guttatus) favor simple frequency ratios derived from the harmonic (or overtone) series. Furthermore, we show that this frequency selection results not from physical constraints governing peripheral production mechanisms but from active selection at a central level. These data provide the most rigorous empirical evidence to date of a bird song that makes use of the same mathematical principles that underlie Western and many non-Western musical scales, demonstrating surprising convergence between human and animal "song cultures." Although there is no evidence that the songs of most bird species follow the overtone series, our findings add to a small but growing body of research showing that a preference for small-integer frequency ratios is not unique to humans. These findings thus have important implications for current debates about the origins of human musical systems and may call for a reevaluation of existing theories of musical consonance based on specific human vocal characteristics.
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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 | 0.004 |
| 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 | 0.001 | 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".