Subdividing the Beat: Auditory and Motor Contributions to Synchronization
Bibliographic record
Abstract
THE CURRENT STUDY EXAMINED HOW AUDITORY AND kinematic information influenced pianists' ability to synchronize musical sequences with a metronome. Pianists performed melodies in which quarter-note beats were subdivided by intervening eighth notes that resulted from auditory information (heard tones), motor production (produced tones), both, or neither. Temporal accuracy of performance was compared with finger trajectories recorded with motion capture. Asynchronies were larger when motor or auditory sensory information occurred between beats; auditory information yielded the largest asynchronies. Pianists were sensitive to the timing of the sensory information; information that occurred earlier relative to the midpoint between metronome beats was associated with larger asynchronies on the following beat. Finger motion was influenced only by motor production between beats and indicated the influence of other fingers' motion. These findings demonstrate that synchronization accuracy in music performance is influenced by both the timing and modality of sensory information that occurs between beats.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".