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Record W2913031394 · doi:10.33137/cpoj.v1i2.32027

RESEARCH PRODUCTIVITY TRENDS IN PROSTHETICS AND ORTHOTICS IN CANADA

2018· article· en· W2913031394 on OpenAlexaffvenueabout
Hossein Gholizadeh, Nader Ale Ebrahim, Arezoo Eshraghi, Edward D. Lemaire

Bibliographic record

VenueCanadian Prosthetics & Orthotics Journal · 2018
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsUniversity of OttawaHolland Bloorview Kids Rehabilitation HospitalOttawa Hospital
Fundersnot available
KeywordsOrthoticsAssistive technologyProductivityQuality of life (healthcare)MedicineGerontologyPhysical therapyPsychologyEngineeringComputer scienceNursing

Abstract

fetched live from OpenAlex

INTRODUCTION
 The Canadian Survey on Disability reported about 3.8 million Canadians between 15 and 64 years lived with a disability in 20121, and more than 80% used an assistive device. Innovation, research, and unrestricted access to knowledge in prosthetics and orthotics is vital to improve a person’s quality of life, removing barriers, and integrating people with functional and mobility limitations into their society. Therefore, this study examined trends in prosthetics and orthotics research in Canada.
 Abstract PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/32027/24444
 How to cite: Gholizadeh H , Ale Ebrahim N, Eshraghi A, Lemaire E.D. RESEARCH PRODUCTIVITY TRENDS IN PROSTHETICS AND ORTHOTICS IN CANADA. 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. 
 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)0.002
metaresearch head score (Gemma)0.000
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 score0.688
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.017
GPT teacher head0.257
Teacher spread0.240 · 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

Citations0
Published2018
Admission routes3
Has abstractyes

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