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Record W2149474875 · doi:10.1682/jrrd.2006.08.0097

Effects of camber on wheeling efficiency in the experienced and inexperienced wheelchair user

2007· article· en· W2149474875 on OpenAlexaff
Angeliki Perdios, Bonita Sawatzky, A. William Sheel

Bibliographic record

VenueThe Journal of Rehabilitation Research and Development · 2007
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsWheelchairWheelingCamber (aerodynamics)Physical medicine and rehabilitationPhysical therapyEnergy expenditureAutomotive engineeringEngineeringPsychologySimulationMedicineComputer scienceStructural engineering

Abstract

fetched live from OpenAlex

The objective of this study was to determine whether energy costs differed between 0 degrees , 3 degrees , and 6 degrees of camber during steady state overground wheeling. Three subject groups were examined: experienced wheelchair users with disabilities (thoracic lesion level 6 and below), nondisabled individuals with manual wheeling experience, and nondisabled individuals with no manual wheeling experience. Heart rate, rating of perceived exertion, visual analog scale for comfort, and a user preference questionnaire were collected for all subjects. Expired gas analysis data were collected for the group with disabilities. No statistically significant differences emerged in respiratory measures for camber angle or group. A camber of 6 degrees was most preferred in terms of stability on a side slope, hand comfort on the pushrims, maneuverability, and overall preference. Rear-wheel camber angle did not affect the energy expenditure of manual wheelchair propulsion, as measured by cardiopulmonary means. The individual manual wheelchair user's perceived level of comfort should be the determining factor in rear-wheel camber selection.

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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0020.000

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 head0.041
GPT teacher head0.416
Teacher spread0.375 · 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

Citations24
Published2007
Admission routes1
Has abstractyes

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