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Record W2323510964 · doi:10.2490/jjrm1963.40.363

Evaluation of Gross Motor Function Level Using Simple Motor Test for Cerebral Palsy in Children with Cerebral Motor Disorders Elucidated by Multi-center Survey

2003· article· en· W2323510964 on OpenAlexaff
Yoshimi Asagai, Izumi Kondo, Shunji Ohshita, Toshirou Okagawa

Bibliographic record

VenueThe Japanese Journal of Rehabilitation Medicine · 2003
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsiNano Medical (Canada)
Fundersnot available
KeywordsCerebral palsyMotor functionPhysical medicine and rehabilitationMedicineTest (biology)AudiologyGross motor skillMotor areaNeuroscienceMotor skillPsychologyBiology

Abstract

fetched live from OpenAlex

12肢体不自由児施設における母子入所117例,外来通院277例の脳性運動障害児粗大運動レベルの変化についてSMTCP領域および運動レベル別評価を用いて検討した.SMTCP運動レベル1段階の向上は,母子入所脳性麻痺例に最も多くみられ,きめ細かな集中したかかわりにより,重度脳性麻痺例であっても確実に向上が期待できることを示している.向上しやすい運動レベルには疾患や重症度により特長はあるものの,「0:全くできない」段階から1段階,2段階向上させ,日常でできるレベルにするための療育プログラムが重要となると考えられた.一方,運動レベルの悪化した項目は,外来脳性麻痺例に多く,母子入所例には少なかった.外来での悪化例に対しては,日常で実施できる指導を行い,在宅での実施状況を再確認し,児や保護者の状況により外来訓練指導回数を増やす,入所集中訓練を実施するなどのきめ細かな対応が必要であると考えられた.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.047
GPT teacher head0.321
Teacher spread0.274 · 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

Citations0
Published2003
Admission routes1
Has abstractyes

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