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Presence of Markers of Femoroacetabular Impingement in the Asymptomatic Population

2009· article· en· W182348863 on OpenAlexaff
Charys Megan Raynor, Dianne Bryant, Alison R. Spouge, Trevor B. Birmingham, Kevin Willits

Bibliographic record

VenueThe FASEB Journal · 2009
Typearticle
Languageen
FieldMedicine
TopicHip disorders and treatments
Canadian institutionsWestern University
FundersSociety of Interventional Radiology Foundation
KeywordsFemoroacetabular impingementAsymptomaticMedicinePopulationInternal medicinePhysical therapy

Abstract

fetched live from OpenAlex

Purpose To determine: 1) the prevalence of femoroacetabular impingement (FAI) in asymptomatic individuals, and 2) whether there is an association between the presence of FAI and age and degenerative disease. Methods: 88 volunteers were verified as asymptomatic through physical examination and then underwent an MRI of the hip. Different criteria values were used to classify the presence or absence of cam (alpha angle of 45, 50 and 55 degrees) and pincer (centre‐edge (CE) angle of 35 and 40 degrees) impingement. Results The prevalence of FAI ranged from 23.9 to 67.0% depending on the classification criteria applied. There was no significant association between FAI and age. Prevalence of FAI, identified using high criteria values (55 degree alpha angle and 40 degree CE angle), predicts the presence of acetabular cartilage lesions. Prevalence of FAI, identified using lower criteria values, was not a significant predictor of degenerative disease. Conclusion FAI is prevalent in the asymptomatic population. Further research is necessary to verify the validity and reliability of criteria used to diagnose impingement and to determine the validity of the diagnosis. Support: AANA and SIRF. Grant Funding Source Internal

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.283
Teacher spread0.267 · 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 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
Published2009
Admission routes1
Has abstractyes

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