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Record W2120941930 · doi:10.1177/0883073814533151

Emerging Therapy Approaches

2014· review· en· W2120941930 on OpenAlexaff
Mary Law, Johanna Darrah

Bibliographic record

VenueJournal of Child Neurology · 2014
Typereview
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsUniversity of AlbertaMcMaster University
Fundersnot available
KeywordsPsychological interventionCerebral palsyRehabilitationIntervention (counseling)Occupational therapyPsychologyConceptual frameworkMedicinePhysical medicine and rehabilitationPhysical therapyNursingSociology

Abstract

fetched live from OpenAlex

Children and youth with cerebral palsy receive ongoing physical and occupational therapy services to improve their functional performance and participation in activities at home, school, and in the community. Over the past 2 decades, rehabilitation interventions have become more functional and goal oriented. In this article, we discuss factors that have influenced emerging intervention approaches. These factors include greater involvement of families in decision making, changing conceptual frameworks and theories underlying skill development and improved outcome measures. New research findings indicate that rehabilitation interventions embracing family-centered services and focusing on functional improvement can be more effective in promoting participation. This knowledge can serve as the platform for further examination of the most effective rehabilitation interventions for children and youth with cerebral palsy.

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: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0240.009

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 head0.067
GPT teacher head0.324
Teacher spread0.257 · 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
GenreReview

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

Citations72
Published2014
Admission routes1
Has abstractyes

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