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Two-incision Total Hip Arthroplasty

2005· review· en· W2078447536 on OpenAlexaff
Michael Tänzer

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2005
Typereview
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineArthroplastyTotal hip arthroplastyOrthopedic surgerySports medicineSurgeryHip surgeryPhysical therapy

Abstract

fetched live from OpenAlex

UNLABELLED: The two-incision total hip arthroplasty is a surgical technique that combines two standard orthopaedic surgical approaches with fluoroscopic guidance, conventional hip implants, and specialized instrumentation. The goal of this procedure is to minimize soft tissue trauma, thereby reducing postoperative morbidity and accelerate rehabilitation. Early reports in the literature have demonstrated a varying incidence of traditional complications and the emergence of additional potential intraoperative complications. We will review the two-incision total hip arthroplasty surgical technique and identify potential pitfalls. Specific recommendations on how to avoid these surgical pitfalls will be described so as to minimize the surgeon's risk of having a complication. LEVEL OF EVIDENCE: Level V (expert opinion). See the Guidelines for Authors for a complete description of levels of evidence.

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)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.002

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 head0.183
GPT teacher head0.500
Teacher spread0.318 · 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
GenreReview

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

Citations6
Published2005
Admission routes1
Has abstractyes

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