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Record W2662461280 · doi:10.1097/bte.0000000000000069

Lesser Tuberosity Osteotomy Versus Subscapularis Peel

2016· article· en· W2662461280 on OpenAlexaff
Matt MacEwan, George S. Athwal, Peter Lapner

Bibliographic record

VenueTechniques in Shoulder & Elbow Surgery · 2016
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsOttawa HospitalHand and Upper Limb ClinicUniversity of Ottawa
Fundersnot available
KeywordsMedicineOsteotomyArthroplastySurgeryOrthodontics

Abstract

fetched live from OpenAlex

Failure of the subscapularis to heal following shoulder arthroplasty can compromise the success of the procedure and may result in pain, instability, and weakness. Options for subscapularis management during exposure include lesser tuberosity osteotomy, subscapularis peel, and subscapularis tenotomy. The optimal approach to subscapularis management remains controversial. The techniques for lesser tuberosity osteotomy and subscapularis peel are described.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.811
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.056
GPT teacher head0.339
Teacher spread0.283 · 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 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

Citations2
Published2016
Admission routes1
Has abstractyes

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