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Record W2030156407 · doi:10.1080/16864360.2014.914375

Simulation Methods in the Foot Orthosis Development Process

2014· article· en· W2030156407 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueComputer-Aided Design and Applications · 2014
Typearticle
Languageen
FieldMedicine
TopicDiabetic Foot Ulcer Assessment and Management
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsFoot (prosody)Computer scienceProcess (computing)Physical medicine and rehabilitationMedicine

Abstract

fetched live from OpenAlex

Traditional methods for developing foot orthoses require extensive skilled manual labor.More modern methods have sought to address this with the introduction of computer enabled technologies such as digital scanning, computer aided design, and automated manufacturing.The current work further advances the process with the introduction of an additional computer enabled technology, simulation models, into two additional steps.First, a simulation model is used to achieve the postural adjustments to the foot normally done by a practitioner.This has the benefit of further automating the process, improving repeatability, and preventing the deformation of the plantar soft tissues that normally occurs with physical postural adjustment.Second, the simulation model is used in a routine to optimize plantar pressure distribution.When compared to a conventional method, the proposed approach yielded a 61% reduction in peak plantar pressure.Future work includes automating the optimization routines for a variety of metrics.Other applications for the current work include the development processes of orthoses and prostheses for other parts of the body.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.978
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.053
GPT teacher head0.383
Teacher spread0.330 · 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