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Record W4214527384 · doi:10.2147/orr.s348726

Optimal Management of Partial Thickness Rotator Cuff Tears: Clinical Considerations and Practical Management

2022· article· en· W4214527384 on OpenAlexaff

Bibliographic record

VenueOrthopedic Research and Reviews · 2022
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsRotator cuffTearsAcromioplastyTendonRotator cuff injuryCuff

Abstract

fetched live from OpenAlex

Partial thickness rotator cuff tears have been diagnosed with increased frequency due to heightened awareness and an improvement in diagnostic modalities. When >50% of the tendon thickness has ruptured, intra-tendinous strain of the residual tendon increases. Surgery is generally confined to patients who have failed non-operative measures and have persistent symptoms. The rationale for repairing partial thickness tears lies in their limited self-healing capacity, and propensity to enlarge over time and progress to a full thickness defect. Although tear debridement and acromioplasty can improve pain and function, tear progression can occur, in addition to worse results being noted in bursal-sided defects. Several surgical strategies have been recommended but there is a lack of evidence to advocate one form of treatment over another. The aim of this narrative review is to discuss the treatment options for partial thickness tears of the rotator cuff.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.810
Threshold uncertainty score0.859

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.261
GPT teacher head0.521
Teacher spread0.260 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations11
Published2022
Admission routes1
Has abstractyes

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