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Record W2022632208 · doi:10.1310/sci1802-138

Wheelchair Skill Performance of Manual Wheelchair Users With Spinal Cord Injury

2012· article· en· W2022632208 on OpenAlexaff
M. Oyster, I. Smith, R. Lee Kirby, Rory A. Cooper, Suzanne L. Groah, Jessica Presperin Pedersen, Michael L. Boninger

Bibliographic record

VenueTopics in Spinal Cord Injury Rehabilitation · 2012
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsWheelchairManual wheelchairSpinal cord injuryPhysical medicine and rehabilitationMedicinePhysical therapySpinal cordComputer science

Abstract

fetched live from OpenAlex

Many individuals with a spinal cord injury (SCI) rely on their wheelchairs to complete daily mobility tasks. Unfortunately, the natural environment creates many mobility challenges for wheelchair users. A study by Meyers et al found that wheelchair users reported curbs, uneven terrain, and travel surface as barriers to their mobility.1 To negotiate these mobility tasks, wheelchair users require certain wheelchair skills. A study by Kilkens et al found wheelchair skills performance to be moderately associated with participation.2 Therefore, the inability to perform certain skills can limit a wheelchair user’s functional independence and participation in daily activities. The purpose of this study was to examine wheelchair skill performance of manual wheelchair users with SCI among 6 Model SCI Systems (MSCIS).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.035
GPT teacher head0.389
Teacher spread0.355 · 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 teacher head, not a consensus.

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

Citations16
Published2012
Admission routes1
Has abstractyes

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