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Record W4392180048 · doi:10.29333/ejgm/14285

Differences in movement patterns related to anterior cruciate ligament injury risk in elite judokas according to sex: A cross-sectional clinical approach study

2024· article· en· W4392180048 on OpenAlexaff
Francisco J Prados-Barbero, Eleuterio A. Sánchez Romero, Juan Nicolás Cuenca‐Zaldívar, Francisco Selva-Sarzo

Bibliographic record

VenueElectronic Journal of General Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsHealth Research Foundation
Fundersnot available
KeywordsAnterior cruciate ligamentACL injuryMedicinePhysical medicine and rehabilitationInternal rotationAnkleValgusExternal rotationPhysical therapySquatAnkle dorsiflexionAthletesMovement controlRange of motionSurgery

Abstract

fetched live from OpenAlex

The anterior cruciate ligament (ACL) injury stands as a significant concern in judo, necessitating preventive measures. The primary injury mechanism involves knee collapse in valgus, often linked to deficiencies in core strength, neuromuscular control, external rotators, hip abductors, and limitations in ankle and hip mobility. Sex-wise, the injury is more prevalent in women across various sports. Therefore, in the present study we observed this possible intersexual disparity in the difference of movement patterns among elite judokas according to their sex, in order to identify those athletes with a higher risk of ACL injury. Notably, there were no discernible differences between sexes in the single leg squat test. Both men and women exhibited compromised neuromuscular control in the non-dominant leg. While ankle dorsiflexion and hip external rotation showed no gender disparities, differences in internal rotation were noted. This particular movement restriction may elevate the risk of ACL injury.

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)0.005
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.705

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.022
GPT teacher head0.379
Teacher spread0.358 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations12
Published2024
Admission routes1
Has abstractyes

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