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Record W4391814399 · doi:10.1080/19424280.2024.2316345

The influence of midsole thickness on running turns

2024· article· en· W4391814399 on OpenAlex
Zach B. Barrons, John W. Wannop, Darren J. Stefanyshyn

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

VenueFootwear Science · 2024
Typearticle
Languageen
FieldEngineering
TopicLower Extremity Biomechanics and Pathologies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsDistance runningSimulationPlane (geometry)Structural engineeringMaterials scienceEngineeringMathematicsPhysical medicine and rehabilitationGeometryMedicine

Abstract

fetched live from OpenAlex

Running race courses typically feature numerous turns, an element of a race typically neglected. If a thick midsole were to decrease frontal plane ankle stability, it could potentially lead to a misalignment of lower limb joints, thereby affecting turn running and overall race performance. Therefore, the purpose of this study was to determine the influence of midsole thickness on turn running performance and peak frontal plane ankle angle. Thirteen recreational athletes participated in this study, which examined the effects of two footwear conditions: one with a 35-mm thick midsole and the other with a 50-mm thick midsole. Participants performed ten running trials around each of three turns of radii 3, 6 and 9 m. No significant differences were found between footwear conditions with respect to time to completion (p = 0.028), centre of mass velocity (p = 0.179) or frontal plane ankle angle (p = 0.935) across any of the three turns. These findings would suggest footwear manufactures need not consider the impact of midsole thickness on turn running performance when designing advanced footwear technology (AFT) and consumers need not avoid a substantial stack height when purchasing running shoes.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.530
Threshold uncertainty score0.166

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.234
Teacher spread0.224 · 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