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Record W4308352119 · doi:10.3390/healthcare10112207

Auditory Cueing of Pre-Learned Skills and Role of Subcortical Information Processing to Maximize Rehabilitative Outcomes Bridging Science and Music-Based Interventions

2022· article· en· W4308352119 on OpenAlexfundno aff
Concetta M. Tomaino

Bibliographic record

VenueHealthcare · 2022
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsnot available
FundersSchool of Humanities and Sciences, Stanford UniversitySchool of Medicine, Stanford UniversityUniversity of Toronto
KeywordsBridging (networking)Psychological interventionPsychologyInformation processingCognitive psychologyMedical educationApplied psychologyCognitive scienceComputer scienceMedicinePsychiatry

Abstract

fetched live from OpenAlex

Auditory entrainment of motor function is a fundamental tool in neurologic music therapy with many studies demonstrating improved clinical outcomes in people with movement disorders such as Parkinson's Disease, acquired brain injuries, and stroke. However, the specific mechanisms of action within neural networks and cortical regions that are aroused and influenced by auditory entrainment still need to be identified. This paper draws from some contemporary neuroscience studies that indicate the role of the cerebellum and other subcortical systems in modulating pre-learned motor schema and proposes a possible rationale for the success of auditory entrainment within neurologic music therapy.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.034
GPT teacher head0.386
Teacher spread0.352 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations7
Published2022
Admission routes1
Has abstractyes

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