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Record W2064419405 · doi:10.5978/islsm.14.171

SUPPRESSION OF MYOTONIA IN CEREBRAL PALSY AND ADJUNCTIVE EFFECT OF LOW LEVEL LASER THERAPY ON INTENSIVE FUNCTIONAL TRAINING

2005· article· en· W2064419405 on OpenAlexaff
Yoshimi Asagai, Yasutaka Watanabe, Toshio Ohshiro, Kengo Yamamoto

Bibliographic record

VenueLASER THERAPY · 2005
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsiNano Medical (Canada)
Fundersnot available
KeywordsMedicineGross Motor Function Classification SystemCerebral palsyPhysical therapyRehabilitationPhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

This study assesses successively the changes in gross movement by hospital treatment with intensive functional training for 1-2 months according to the objective assessment criteria, the gross motor function measure (GMFM), which is commonly accepted as the global standard. Intensive functional training was carried out on its own in institutions other than the principal author’s, or together with low reactive-level IR diode laser therapy (LLLT) in the Shinano Handicapped Children’s Hospital, and the efficacy of the two approaches was compared. The severity of the disease was classified according to the gross motor function classification system (GMFCS). When the development of motor function was compared separately by disease severity with the cross-sectional motor growth curve, in the cases of the GMFCS level III a significant improvement was observed in patients of up to around age 8 . A significant improvement was observed inpatients of up to around 8 years old, especially up to 3 years old, when compared with the cross-sectional motor growth curve even when the GMFCS level was IV. When compared with patients at other rehabilitation and training sites, where only functional training therapy was applied without LLLT, the efficacy of intensive functional training was clearly enhanced in combination with LLLT.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.358
Threshold uncertainty score0.600

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.038
GPT teacher head0.281
Teacher spread0.243 · 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 teacher head, 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

Citations8
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueLASER THERAPYSame topicCerebral Palsy and Movement DisordersFrench-language works237,207