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Record W2171581517 · doi:10.1111/nyas.12717

Motor responses to a steady beat

2015· article· en· W2171581517 on OpenAlexaff
Rebecca Schaefer, Katie Overy

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2015
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsWestern University
FundersEuropean Commission
KeywordsBeat (acoustics)ChemistryMedicinePhysicsAcoustics

Abstract

fetched live from OpenAlex

It is increasingly well established that music containing an isochronous pulse elicits motor responses at the levels of both brain and behavior. Such motor responses are often used in pedagogical and clinical practice to induce movement, particularly where motor functions are impaired. However, the complex nature of such apparently universal human responses has, arguably, not received adequate research attention to date. In particular, it should be noted that many adults, including those with disabilities, find it somewhat difficult to synchronize their movements with a beat with perfect accuracy; indeed, perfecting the skill of being musically "in time" can take years of training during childhood. Further research is needed on the nature of both the specificity and range of motor responses that can arise from the perception of a steady auditory pulse, with different populations, musical stimuli, conditions, and required levels of accuracy in order to better understand and capture the potential value of the musical beat as a pedagogical and therapeutic tool.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.312
GPT teacher head0.404
Teacher spread0.092 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2015
Admission routes1
Has abstractyes

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