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Record W3198342566 · doi:10.7759/cureus.17525

Bilateral Arthroscopic Superior Capsular Reconstruction of the Shoulder for Irreparable Rotator Cuff Tears: A Case Report and Description of Surgical Technique

2021· article· en· W3198342566 on OpenAlexaff
Waleed Albishi, Khalid Murrad, Amr Elmaraghy

Bibliographic record

VenueCureus · 2021
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineRotator cuffTearsSurgeryRange of motionArthroscopyCuffRotator cuff injury

Abstract

fetched live from OpenAlex

The treatment strategies for rotator cuff tears have grown more sophisticated in recent years. Over the past decade, arthroscopic superior capsular reconstruction (SCR) has become popular for treating irreparable rotator cuff tears. Despite the popularity, the literature on the clinical outcomes of SCR is limited. Several surgical procedures using variable graft materials and different techniques have been proposed promising early clinical results with improvements in shoulder pain, range of motion, and overall function. In this paper, we present a case of bilateral massive irreparable rotator cuff tears, with a full description of our surgical technique and the successful outcome of our management.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0020.002
Scholarly communication0.0010.002
Open science0.0020.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.032
GPT teacher head0.314
Teacher spread0.282 · 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 designCase report
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
Published2021
Admission routes1
Has abstractyes

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