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Record W6978060987 · doi:10.7939/dvn/10923

Evaluation of the Effectiveness of Robotic Gait Training and Gait-focused Physical Therapy Programs for Children and Youth With Cerebral Palsy: A Mixed Methods Randomized Controlled Trial

2016· dataset· en· W6978060987 on OpenAlexaff

Bibliographic record

VenueBorealis · 2016
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of AlbertaHolland Bloorview Kids Rehabilitation Hospital
Fundersnot available
KeywordsRandomized controlled trialRehabilitationGait trainingGaitQualitative researchResearch design

Abstract

fetched live from OpenAlex

This is a prospective, multi-centre, concurrent mixed methods study comprised of a randomized controlled trial (RCT) and an interpretive descriptive qualitative design. The goal of the RCT is to compare: 1) a walking training program with the Lokomat robotic device (LOK), 2) a functional physical therapy program (fPT) that includes activities to enhance balance/co-ordination/endurance and advanced motor skills conducted over 'real ground', 3) a combined Lokomat + functional physical therapy (LOK+fPT) program, and 4) a regular maintenance therapy condition (CONT). The qualitative part of the study will consist of interviews of children and parents after they have finished the study intervention.

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)0.021
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.045
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.006
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0280.002

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 head0.046
GPT teacher head0.344
Teacher spread0.298 · 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 designRandomized trial
Domainnot available
GenreDataset

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
Published2016
Admission routes1
Has abstractyes

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