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Record W4417138184 · doi:10.51249/hs.v5i06.2744

NEUROLOGICAL MUSIC THERAPY (NMT) IN AUTISM SPECTRUM DISORDER (ASD)

2025· article· W4417138184 on OpenAlexaboutno aff

Bibliographic record

VenueHealth and Society · 2025
Typearticle
Language
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsnot available
Fundersnot available
KeywordsNeurorehabilitationMusic therapyAutism spectrum disorderAutismRehabilitationPsychological intervention

Abstract

fetched live from OpenAlex

Autistic Spectrum Disorder (ASD) involves persistent changes in communication, social interaction and restricted and repetitive patterns of behavior. Neurological Music Therapy (Neurologic Music Therapy - NMT) is an international therapeutic model based on neuroscience, composed of 20 standardized techniques that allow measurable interventions in the motor, linguistic and cognitive domains. This article deepens the neurobiological mechanisms underlying the NMT and discusses its applications in ASD, gathering recent scientific evidence that points to gains in motor coordination, attention, engagement and functional communication. Internationally, NMT is recognized as evidence-based practice and used in rehabilitation centers in Canada, the United States and Europe. In Brazil, however, its diffusion is still limited. Based on the experience of the author - neuropsychologist, neurotherapist, behavioral analyst, member of the World Federation for NeuroRehabilitation (WFNR), autistic individual and father of autistic children - this work proposes the NMT as a valid, safe and necessary tool in the field of neurorehabilitation and autism.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.039
GPT teacher head0.360
Teacher spread0.321 · 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
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

Citations0
Published2025
Admission routes1
Has abstractyes

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