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Record W3122805022 · doi:10.1016/j.eats.2020.10.043

Repair of Symptomatic Partial Gluteus Medius Tear During Total Hip Arthroplasty Through the Direct Anterior Approach

2021· article· en· W3122805022 on OpenAlexfundno aff
David R. Maldonado, Samantha C. Diulus, Mitchell B. Meghpara, Rachel M. Glein, Hari K. Ankem, Ajay C. Lall, Benjamin G. Domb

Bibliographic record

VenueArthroscopy Techniques · 2021
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsnot available
FundersUniversity of Illinois at Urbana-ChampaignPacira BioSciencesPacira PharmaceuticalsArthroscopy Association of North AmericaMAKO Surgical CorporationStrykerGraymontCharles E. Kaufman FoundationArthrexAllegheny Technologies Incorporated
KeywordsMedicineMediusTearsTotal hip arthroplastySurgeryHip painArthroplasty

Abstract

fetched live from OpenAlex

Gluteus medius (GM) tears are a well-established source of pain and disability. Considering previous studies, which have reported rates of incidental GM tears in 20% of patients undergoing primary total hip arthroplasty (THA) and a 3-fold greater rate in elderly female patients, additional focus should be placed on identifying treatment options. The direct anterior approach (DAA) for primary THA has gained popularity within the past few years. However, there has been a paucity in the literature on how to address symptomatic and partial GM tears through this approach. The purpose of this Technical Note is to describe a method to repair partial GM tears during primary THA using the DAA.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.234
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.271
Teacher spread0.259 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations6
Published2021
Admission routes1
Has abstractyes

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