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Effects of shoe sole construction on skeletal motion during running

2001· article· en· W1985321218 on OpenAlexaff
Alex Stacoff, C. Reinschmidt, Benno M. Nigg, Antonie J. van den Bogert, J. Denoth, E. Stüssi

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2001
Typearticle
Languageen
FieldEngineering
TopicLower Extremity Biomechanics and Pathologies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMotion (physics)Physical medicine and rehabilitationComputer scienceMedicineArtificial intelligence

Abstract

fetched live from OpenAlex

PURPOSE: The purpose of this study was to quantify effects of shoe sole modification on skeletal kinematics of the calcaneus and tibia during the stance phase of running. METHODS: Intracortical bone pins with reflective marker triads were inserted under standard local anesthetic into the calcaneus and tibia of five healthy male subjects. The three-dimensional tibiocalcaneal rotations were determined using a joint coordinate system approach. Three shoe sole modifications were tested with different sole geometry: a lateral heel flare of 25 degrees (flared), no flare 0 degrees (straight), and a rounded sole. RESULTS: The results showed that these shoe sole modifications did not change tibiocalcaneal rotations substantially. The shoe sole effects at the bone level were small and unsystematic (mean effects being less than 1 degrees ) compared with the differences between the subjects (up to 7 degrees ). Shoe eversion measured simultaneously with shoe markers showed no systematic shoe sole effects. A comparison of shoe and bone results showed the total shoe eversion and maximum shoe eversion velocity to be approximately twice as large as the respective measurements based on bone markers (correlations being r = 0.79 for maximum eversion velocity; r = 0.88 for total eversion), indicating that there may be a relationship or coupling effect between the shoes and the bone. CONCLUSIONS: It is concluded that the tibiocalcaneal kinematics of running may be individually unique and that shoe sole modifications may not be able to change them substantially.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.007
GPT teacher head0.224
Teacher spread0.216 · 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 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

Citations113
Published2001
Admission routes1
Has abstractyes

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