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Record W2912674185 · doi:10.33137/cpoj.v1i2.32028

EVALUATION OF LOCALIZED PAIN IN THE TRANSTIBIAL RESIDUAL LIMB

2018· article· en· W2912674185 on OpenAlexvenueaboutno aff
Kamiar Ghoseiri, Mohammad Yusuf Rastkhadiv, Mostafa Allami

Bibliographic record

VenueCanadian Prosthetics & Orthotics Journal · 2018
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsnot available
Fundersnot available
KeywordsProsthesisMedicinePhysical medicine and rehabilitationPhysical therapyOrthoticsSurgery

Abstract

fetched live from OpenAlex

PURPOSE
 The socket is the main component of a prosthesis which surrounds the residual limb and transfers loads and motions between the residual limb and prosthesis. A misfit socket may lead to excessive stresses on the residual limb, pistoning of the prosthesis during walking, patient discomfort, pain, and skin damage. The quality of socket-skin interface directly affects quality of life, prosthesis use, and satisfaction from prosthesis in amputees. Pain is a devastating condition that prohibits prosthesis use1-4. The present study aimed to evaluate pain threshold and tolerance of the transtibial residual limb to improve its socket design and fit. 
 Abstract PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/32028/24445
 How to cite: Ghoseiri K, Rastkhadiv M.Y, Allami M. EVALUATION OF LOCALIZED PAIN IN THE TRANSTIBIAL RESIDUAL LIMB. CANADIAN PROSTHETICS & ORTHOTICS JOURNAL, VOLUME 1, ISSUE 2, 2018; ABSTRACT, ORAL PRESENTATION AT THE AOPA’S 101ST NATIONAL ASSEMBLY, SEPT. 26-29, VANCOUVER, CANADA, 2018. DOI: https://doi.org/10.33137/cpoj.v1i2.32028 
 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)0.008
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.481
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
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)0.0000.000

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 head0.020
GPT teacher head0.250
Teacher spread0.230 · 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 designSimulation or modeling
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

Citations5
Published2018
Admission routes2
Has abstractyes

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