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Record W2810452978 · doi:10.1177/0748730418783651

Musicians’ Natural Frequencies of Performance Display Optimal Temporal Stability

2018· article· en· W2810452978 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Biological Rhythms · 2018
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsMcGill University
FundersFonds Québécois de la Recherche sur la Nature et les TechnologiesNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsStability (learning theory)Natural (archaeology)Computer scienceBiologyMachine learning

Abstract

fetched live from OpenAlex

Many human action sequences, such as speaking and performing music, are inherently rhythmic: Sequence events are produced at quasi-regular temporal intervals. A wide range of interindividual variation has been noted in spontaneous production rates of these rhythmic action sequences. Dynamical theories of motor coordination suggest that individuals spontaneously produce rhythmic sequences at a natural frequency characterized by minimal energy expenditure and maximal temporal stability, relative to other frequencies. We tested this hypothesis by comparing the temporal variability with which musicians performed rhythmic melodies at their natural spontaneous rate with variability in their performances at faster and slower rates. Musicians' temporal variability was lowest during performances at their spontaneous rate; in addition, performers' tempo drift during trials at other rates showed bias toward their spontaneous rate. This study provides the first direct evidence that spontaneous rates of motor coordination represent optimally stable natural frequencies of endogenous rhythms.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.298
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.082
GPT teacher head0.299
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it