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Record W2913781477 · doi:10.33137/cpoj.v1i2.30813

THE IMPORTANCE OF ADDITIONAL MID SWING TOE CLEARANCE FOR AMPUTEES

2018· article· en· W2913781477 on OpenAlexvenueaboutno aff
Knut Lechler, Kristleifur Kristjánsson

Bibliographic record

VenueCanadian Prosthetics & Orthotics Journal · 2018
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsnot available
Fundersnot available
KeywordsSwingPhysical medicine and rehabilitationGaitMedicineOsteoarthritisProsthesisPhysical therapyEngineeringSurgeryMechanical engineering

Abstract

fetched live from OpenAlex

Increased prosthetic hip to toe distance and insufficient mid swing toe clearance of a prosthetic foot is a well-recognized inadequacy for lower limb prosthesis users with wide and possible grave consequences on their ambulation capabilities. Most important are increased risk of falls and abnormal compensatory gait patterns with secondary unwanted physical effect like generally deceased mobility, muscular-skeletal pain and joint degeneration, i.e. osteoarthritis, with possible significant health economic effect. Even though insufficient toe clearance can be device related and technically or even intentionally induced for attaining equal length of the lower extremities in a neutral standing position or the stance phase, it is important to be aware of available technical solutions that can counteract the problem, like swing phase dorsiflexing feet, vacuum suspension systems, polycentric axis knees rather than single-axis knees and adequate knee flexion in early swing and swing-flexion assistance in the case of bionic knees.
 Article PDf Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/30813/23259
 How to cite: Lechler K, and Kristjansson K. The importance of additional mid swing toe clearance for amputees. Canadian Prosthetics & Orthotics Journal. Volume1, Issue2, No.1, 2018. DOI: https://doi.org/10.33137/cpoj.v1i2.30813

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.490
Threshold uncertainty score0.530

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 head0.008
GPT teacher head0.215
Teacher spread0.207 · 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 designNot applicable
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

Citations10
Published2018
Admission routes2
Has abstractyes

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