Asymmetries in the Discrimination of Musical Intervals: Going Out-of-Tune Is More Noticeable Than Going In-Tune
Bibliographic record
Abstract
Listeners were tested on their ability to discriminate "standard" and "comparison" pure-tone musical intervals that differed in size by 20 cents (1/ 5 of an equal-tempered semitone). Some of the intervals were prototypic, equal-tempered perfect fifths (exactly 7 semitones, or 700 cents). Others were mistuned to various degrees (660, 680, 720, or 740 cents). The intervals were melodic (sequential) in Experiments 1 and 2 and harmonic (simultaneous) in Experiment 3. Performance was neither enhanced nor impaired in comparisons that included the prototype. In other words, no "perceptual magnet" or "perceptual anchor" effects were observed. Nonetheless, performance was markedly asymmetric. Regardless of listeners' musical expertise, discrimination was superior when the standard interval was more accurately tuned than the comparison interval (e.g., 700- cent standard, 680-cent comparison), compared with when the comparison was more accurately tuned than the standard (e.g., 680-cent standard, 700-cent comparison).
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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 | 0.007 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".