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Record W2044935030 · doi:10.1115/imece2010-39464

A Two-Dimensional Nonlinear Volumetric Foot Contact Model

2010· article· en· W2044935030 on OpenAlexaff
Sukhpreet Singh Sandhu, John McPhee

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicDiabetic Foot Ulcer Assessment and Management
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsHyperelastic materialNonlinear systemKinematicsEllipseOgdenFoot (prosody)Nonlinear modelStructural engineeringHeelComputer scienceMaterials scienceEngineeringMechanicsFinite element methodPhysicsGeometryMathematicsClassical mechanicsComposite material

Abstract

fetched live from OpenAlex

This paper presents the development of a two-dimensional (2D) multibody foot contact model consisting of a volumetric model of foot pad. The volumetric model employs nonlinear springs and linear dampers to represent the complex material behavior of the foot pad, typical of a visco-hyperelastic material. The nonlinear springs of the foot contact model are motivated by an Ogden-type material that can describe the nonlinear constitutive behavior of a wide variety of biological tissues and rubbers. The geometry of the foot pad is modeled as three simplified ellipse which represent the heel, balls of the feet, and toe. The efficacy of the developed foot contact model is established by driving the simulation model with kinematics observed from walking experiments and comparing the generated ground reaction force with the experimental data.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.294
Teacher spread0.278 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2010
Admission routes1
Has abstractyes

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