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Record W2912463047 · doi:10.33137/cpoj.v1i2.32001

I AM THE BOY WITH ONE HAND WHO CAN DO ANYTHING”: PERCEPTIONS OF ABILITY AMONG PEOPLE WITH UPPER LIMB ABSENCE

2018· article· en· W2912463047 on OpenAlexvenueaboutno aff
Cody L. McDonald, Cynthia L. Bennett, Daniela K. Rosner, Katherine M. Steele

Bibliographic record

VenueCanadian Prosthetics & Orthotics Journal · 2018
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsnot available
FundersDivision of Chemical, Bioengineering, Environmental, and Transport SystemsNational Science Foundation
KeywordsCosmesisPerceptionQuality of life (healthcare)PsychologyPresentation (obstetrics)Upper limbGerontologyMedicinePhysical medicine and rehabilitationSurgeryPsychotherapist

Abstract

fetched live from OpenAlex

INTRODUCTION
 Upper limb prostheses are commonly prescribed for people with upper limb absence (ULA) to restore function, cosmesis, and assist with activities of daily living. However, nearly one in five people with ULA chooses not to use a prosthesis1 and instead turns to alternative technology and adaptations, pointing to factors beyond prostheses that shape perceptions of ability and quality of life. We examined through interviews the lived experiences of people with ULA framed around their perceptions of ability, device use, and quality of life.
 Abstract PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/32001/24423
 How to cite: McDonald C.L, Bennett C.L, Rosner D.K, Steele K.M. I AM THE BOY WITH ONE HAND WHO CAN DO ANYTHING”: PERCEPTIONS OF ABILITY AMONG PEOPLE WITH UPPER LIMB ABSENCE. CANADIAN PROSTHETICS & ORTHOTICS JOURNAL, VOLUME 1, ISSUE 2, 2018; ABSTRACT, POSTER PRESENTATION AT THE AOPA’S 101ST NATIONAL ASSEMBLY, SEPT. 26-29, VANCOUVER, CANADA, 2018. DOI: https://doi.org/10.33137/cpoj.v1i2.32001 
 Abstracts were Peer-reviewed by the American Orthotic Prosthetic Association (AOPA) 101st National Assembly Scientific Committee. 
 http://www.aopanet.org/

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.243
Threshold uncertainty score0.768

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.005
GPT teacher head0.188
Teacher spread0.183 · 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.

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
Published2018
Admission routes2
Has abstractyes

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