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Record W147930455 · doi:10.1080/14763140408522830

Athletics

2004· article· en· W147930455 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSports Biomechanics · 2004
Typearticle
Languageen
FieldEngineering
TopicLower Extremity Biomechanics and Pathologies
Canadian institutionsUniversity of Calgary
FundersUniversity of Calgary
KeywordsSprintStiffnessBending stiffnessMathematicsBendingPlyometricsAthletesStructural engineeringOrthodonticsPhysical medicine and rehabilitationPhysical therapyMedicineJumpEngineeringPhysics

Abstract

fetched live from OpenAlex

The purposes of this investigation were to determine if increasing the bending stiffness of sprint shoes increases sprinting performance and to determine whether simple anthropometric factors can be used to predict shoe bending stiffness for optimal performance. Thirty-four athletes were tested using four different shoe conditions--a standard condition consisting of their currently used footwear and three conditions where the bending stiffness was increased systematically. The sprinters performed maximal effort 40 m sprints and their sprint times were recorded from 20 to 40 m. On average, increasing the shoe bending stiffness increased sprint performance. The stiffness each athlete required for his or her maximal performance was subject specific but was not related to subject mass, height, shoe size or skill level. It is speculated that individual differences in the force-length and force-velocity relationships of the calf muscles may influence the appropriate shoe stiffness for each athlete to obtain their maximal performance.

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 score0.403
Threshold uncertainty score0.700

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 studies0.0000.000
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 head0.007
GPT teacher head0.179
Teacher spread0.172 · 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