Bibliographic record
Abstract
In the study of auditory rhythm perception, a key question is the relationship between the perception of a beat and moving to the beat. The most obvious way to observe an individual’s perceived beat is to ask them to move along with it (e.g., tap a finger on the beat). But this type of observation affects the observed percept: experiments show that rhythm perception is altered in several ways during movement, even if that movement is as minimal as a finger tap. In particular, rhythmic movement seems to give perceptual “momentum” to a beat percept, helping it continue and making it robust to input perturbations and complexity. Here, we argue that this phenomenon can be elegantly accounted for by assuming that our perception of a periodic beat is partly entrained by the sensory feedback from our own movement. We show that this under-studied aspect of human rhythm provides a parsimonious explanation for a range of experimental results in healthy and disordered populations; that it poses challenges to existing models of rhythm production and entrainment; and that it may be a key to understanding the role of the cerebellum in sensorimotor synchronization and the observation of synchronization differences in autism.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.014 | 0.005 |
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".