Bibliographic record
Abstract
The parsing of undifferentiated tone sequences into groups of qualitatively distinct elements is one of the earliest rhythmic phenomena to have been investigated experimentally (Bolton, 1894). The present study aimed to replicate and extend these findings through online experimentation using a spontaneous grouping paradigm with forced-choice response (from 1 to 12 tones per group). Two types of isochronous sequences were used: equitone sequences, which varied only with respect to signal rate (200, 550, or 950 ms interonset intervals), and accented sequences, in which accents were added every two or three tones to test the effect of induced grouping (duple vs. triple) and accent type (intensity, duration, or pitch). In equitone sequences, participants’ grouping percepts (N = 4,194) were asymmetrical and tempo-dependent, with “no grouping” and groups of four being most frequently reported. In accented sequences, slower rate, induced triple grouping, and intensity accents correlated with increases in group length. Furthermore, the probability of observing a mixed metric type—that is, grouping percepts divisible by both two and three (6 and 12)—was found to be highest in faster sequences with induced triple grouping. These findings suggest that lower-level triple grouping gives rise to binary grouping percepts at higher metrical levels.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".