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Record W2314850608 · doi:10.1055/s-2006-926640

Gradierung der funktionellen Sportschuhparameter „Dämpfung” und „Vorfußflexibilität” am Laufschuh

2006· article· de· W2314850608 on OpenAlexaff
Frank Kleindienst, Berthold Krabbe, Martina Walther, Gert‐Peter Brüggemann

Bibliographic record

VenueSportverletzung · Sportschaden · 2006
Typearticle
Languagede
FieldMedicine
TopicSports Performance and Training
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsForefootCushioningGrading (engineering)BarefootOperations managementComputer scienceEngineeringPhysical medicine and rehabilitationMedicineMechanical engineeringCivil engineeringSurgery

Abstract

fetched live from OpenAlex

On nearly every running event a heterogeneous structure of participants regarding body height and body weight can be observed. This study should figure out whether the running shoe manufacturers will consider this anthropometric variability. Moreover it should be investigated the runners needs based on different anthropometrics regarding preferred cushioning and forefoot flexibility properties. In order to check whether the running shoe manufacturers will apply a grading pattern, a dynamic material study with conventional running shoes in different sizes was conducted. In a second step a field study in Middle Europe and North America with 244 female and 227 male runners was organized. Every subject had to run and evaluate 7 different shoe modifications. Based on the material study it is to state, that the running shoe manufacturers currently do not consider a systematic grading of cushioning and forefoot flexibility properties. In contrast to this, the field study reveals the necessity to grade these properties. A shoe size dependent and a geographic grading concept are suggested. It is supposed, that the application of these grading concepts do not only provide a comfort improvement, but they also contribute to a reduction of joint loads of the lower extremities and consequently to a prevention of overuse injuries.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.311
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.005

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 head0.014
GPT teacher head0.270
Teacher spread0.256 · 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; both teacher heads agree on what is shown here.

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

Citations3
Published2006
Admission routes1
Has abstractyes

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