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Record W4206756462 · doi:10.1002/9781119413936.ch93

Hip Dislocations

2021· other· en· W4206756462 on OpenAlexaff
Luis López, Carlos Prada MD MHSc, Brett D. Crist, Gregory J. Della Rocca

Bibliographic record

VenueEvidence-Based Orthopedics · 2021
Typeother
Languageen
FieldMedicine
TopicHip disorders and treatments
Canadian institutionsMcMaster UniversitySunnybrook HospitalUniversity of Toronto
Fundersnot available
KeywordsAvascular necrosisMedicineHip arthroscopySurgeryReduction (mathematics)Hip painMotor vehicle crashEmergency departmentArthroscopyPoison controlInjury preventionNursingFemoral headMedical emergency

Abstract

fetched live from OpenAlex

This chapter presents a case scenario of a 40-year-old male who is brought to the Emergency Department after a motor vehicle crash. Traumatic hip dislocations are uncommon but severe injuries mainly observed after motor vehicle crashes and occasionally associated with sporting injuries. Most surgeons believe that rapid reduction of hip dislocations is important to minimize avascular necrosis risk, but this is unproven. Hip dislocations are normally diagnosed with orthogonal plane x-rays. Arthroscopy has emerged as an important therapeutic tool after traumatic hip dislocation to treat some patients with persistent pain or mechanical symptoms associated with intra-articular loose bodies or other injuries, such as labral tears. The arthroscopic treatment of intra-articular pathology with debridement and/or repair after traumatic hip dislocations appears to be safe and effective. The chapter also provides recommendations for implementing evidence-based practice in the clinical setting.

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 score0.019
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0190.005

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 head0.061
GPT teacher head0.333
Teacher spread0.271 · 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
Published2021
Admission routes1
Has abstractyes

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