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Record W4392618179 · doi:10.1097/pep.0000000000001096

Locomotion Efficiency in Children With Cerebral Palsy Experiencing Limited Gross Motor Function: Walking Versus Cycling

2024· article· en· W4392618179 on OpenAlexaff
Cloé Dussault-Picard, Annie Pouliot-Laforte, Claire Cherriere, Eloïse Houle, Laurent Ballaz

Bibliographic record

VenuePediatric Physical Therapy · 2024
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversité du Québec à Montréal
Fundersnot available
KeywordsCyclingCerebral palsyEnergy expenditurePhysical medicine and rehabilitationPreferred walking speedPhysical therapyMedicinePsychologyGeography

Abstract

fetched live from OpenAlex

PURPOSE: This study compares cycling and walking efficiency, and energy expenditure in children with bilateral spastic cerebral palsy (CP). In children with CP, locomotion with body weight support aids such as a tricycle is a potential alternative for less exhausting movements. METHODS: Nine children with CP traveled at comfortable speed for 6 minutes by cycling and walking. The energy expenditure index (EEI) and the percentage of the reserve heart rate (%HRR) were calculated. RESULTS: The EEI was lower while cycling than walking, the traveled distance was higher while cycling than walking, and %HRR remained similar between cycling and walking. CONCLUSION: Cycling appears an efficient alternative to walking for children with CP for adapted school environments and in the community.

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)0.002
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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.018
GPT teacher head0.275
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 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
Published2024
Admission routes1
Has abstractyes

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