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Record W1532062030 · doi:10.1002/9781444345100.ch16

Hip Resurfacing vs. Metal‐On‐Metal Total Hip Arthroplasty

2011· other· en· W1532062030 on OpenAlexaff
Sänket R. Diwanji, Pascal‐André Vendittoli, Martin Lavigne

Bibliographic record

VenueEvidence-Based Orthopedics · 2011
Typeother
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsUniversité de MontréalHôpital Maisonneuve-Rosemont
Fundersnot available
KeywordsAvascular necrosisFemoral headMedicineTotal hip arthroplastyHip resurfacingFemoral neckSurvivorship curveArthroplastySurgeryRange of motionImplantHip arthroplastyPopulationInternal medicineOsteoporosis

Abstract

fetched live from OpenAlex

Metal-on-metal hip resurfacing (HR) is emerging as an alternative to total hip arthroplasty (THA) in young adults with hip degeneration. Existing evidence shows that clinical outcomes and level of activity are similar after HR and Large diameter head (LDH)-THA; controversy persists regarding outcomes of HR and conventional THA. LDH-THA provides better range of motion as compared to HR and conventional THA. Complications such as femoral neck fracture and avascular necrosis of femoral head are unique to HR and are responsible for higher rate of femoral component failure when compared to THA. Metal ion release after HR and 28 mm metal-on-metal (MOM) THA differed in various studies based on implant characteristics. Finally, revision of HR provides clinical outcomes comparable to primary THA, which may be an important advantage in younger population if HR's mid and long term survivorship is proven adequate.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0220.002

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 head0.053
GPT teacher head0.282
Teacher spread0.229 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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