Well-Formed Stimuli Lead to Perceptual Asymmetries in Discrimination: Evidence from Musical Chords and Rhythms
Bibliographic record
Abstract
In three experiments, listeners heard standard and comparison auditory sequences on each trial and judged whether they were the same or different. In Experiments 1 and 2, the sequences comprised chords (i.e., simultaneous combinations of pure tones) that were familiar (major), less familiar but with no sensory dissonance (diminished), or unfamiliar and dissonant. Performance was better in the major condition than in the other two conditions, but only when the major chord was the standard sequence. When it was the comparison, performance was poor. In Experiment 3, the stimuli were metrical or nonmetrical rhythms comprised of snare-drum beats. A discrimination advantage for metrical sequences was evident when the metrical sequence was the standard pattern but not when it was the comparison. In short, order of presentation determined whether well-formed stimuli facilitated discrimination. Well-formed auditory sequences led to advantages in discrimination when they were the standard (presented first), but this advantage was eliminated when the well-formed sequence was the comparison (presented second).
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".