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Record W2135694465 · doi:10.1136/bjsports-2015-095054

Running shoes and running injuries: mythbusting and a proposal for two new paradigms: ‘preferred movement path’ and ‘comfort filter’

2015· review· en· W2135694465 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.

Bibliographic record

VenueBritish Journal of Sports Medicine · 2015
Typereview
Languageen
FieldEngineering
TopicLower Extremity Biomechanics and Pathologies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPhysical medicine and rehabilitationMovement (music)Path (computing)Filter (signal processing)Injury preventionComputer sciencePsychologyMedicinePhysical therapyPoison controlMedical emergencyComputer visionAesthetics

Abstract

fetched live from OpenAlex

In the past 100 years, running shoes experienced dramatic changes. The question then arises whether or not running shoes (or sport shoes in general) influence the frequency of running injuries at all. This paper addresses five aspects related to running injuries and shoe selection, including (1) the changes in running injuries over the past 40 years, (2) the relationship between sport shoes, sport inserts and running injuries, (3) previously researched mechanisms of injury related to footwear and two new paradigms for injury prevention including (4) the 'preferred movement path' and (5) the 'comfort filter'. Specifically, the data regarding the relationship between impact characteristics and ankle pronation to the risk of developing a running-related injury is reviewed. Based on the lack of conclusive evidence for these two variables, which were once thought to be the prime predictors of running injuries, two new paradigms are suggested to elucidate the association between footwear and injury. These two paradigms, 'the preferred movement path' and 'the comfort filter', suggest that a runner intuitively selects a comfortable product using their own comfort filter that allows them to remain in the preferred movement path. This may automatically reduce the injury risk and may explain why there does not seem to be a secular trend in running injury rates.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.042
GPT teacher head0.298
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