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Record W2005799885 · doi:10.1080/19424280902993001

Improved footwear comfort reduces oxygen consumption during running

2009· article· en· W2005799885 on OpenAlexaff
Geng Luo, Pro Stergiou, Jay T. Worobets, Benno M. Nigg, Darren J. Stefanyshyn

Bibliographic record

VenueFootwear Science · 2009
Typearticle
Languageen
FieldEngineering
TopicLower Extremity Biomechanics and Pathologies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsRunning economyConsumption (sociology)Physical medicine and rehabilitationPhysical therapyVO2 maxPsychologySimulationEngineeringMedicineHeart rate

Abstract

fetched live from OpenAlex

Footwear comfort has been shown to have an influence on injuries, but it was unknown whether comfort was related to performance. The current study examined the effects of footwear comfort on running economy. Thirteen male participants rated five pairs of shoes on perceived comfort. Oxygen consumption was assessed during steady state runs in the least and most comfortable shoes at slightly above the aerobic threshold. A paired t-test was used to compare running economy in the most versus the least comfortable shoe conditions. The findings of the study indicated a significant improvement in running economy, 0.7% on average, in the most comfortable shoe condition. It is suggested that future study of kinematic and kinetic reactions to footwear of different comfort will help to understand the mechanism for the observed performance improvement.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

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 head0.016
GPT teacher head0.236
Teacher spread0.220 · 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 designBench or experimental
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

Citations120
Published2009
Admission routes1
Has abstractyes

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