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Record W2913929115 · doi:10.1002/9781444345100.ch104

Hip Impingement

2011· other· en· W2913929115 on OpenAlexaff
Marc J. Philippon, Karen K. Briggs

Bibliographic record

VenueEvidence-Based Orthopedics · 2011
Typeother
Languageen
FieldMedicine
TopicHip disorders and treatments
Canadian institutionsMcMaster University
Fundersnot available
KeywordsFemoroacetabular impingementHip arthroscopyAthletesMedicinePhysical therapyArthroscopyReturn to sportSports medicineKnee arthroscopyHip painPopulationField hockeySurgeryFootball

Abstract

fetched live from OpenAlex

Femoroacetabular impingement is becoming an important diagnosis in the sports medicine population. In order for patients to receive early treatment, a diagnostic algorithm is necessary to ensure proper diagnosis. There are several surgical options for treatment of FAI, however, arthroscopic treatment allows for the patient to return to activities and sport much quicker. FAI commonly causes labral tears and chondral defects. With proper indications, labral repair is supported by level 2 evidence research as the procedure of choice. The young active patient or athlete desires to return to their sport following hip arthroscopy. Currently, level 4 research shows that athletes can expect to return to sport much faster those patients who undergo open procedures. The young active patient experiences improvement in pain and function. Hip arthroscopy is a growing field and more research is expected to further show the efficacy of hip arthroscopy in the sports medicine population.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.037
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0370.005

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 head0.074
GPT teacher head0.315
Teacher spread0.241 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2011
Admission routes1
Has abstractyes

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