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Record W2332083174 · doi:10.1097/jsa.0b013e3182189468

Current Imaging of the Rotator Cuff

2011· review· en· W2332083174 on OpenAlexaff
Steve Gazzola, Robert R. Bleakney

Bibliographic record

VenueSports Medicine and Arthroscopy Review · 2011
Typereview
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsRotator cuffMedicineMagnetic resonance imagingTearsUltrasoundModalitiesRadiologyTendonRotator cuff injuryRadiographySurgery

Abstract

fetched live from OpenAlex

Rotator cuff pathology is a common cause of shoulder pain, and imaging plays a major role in the management of shoulder problems. General radiography may be useful as an initial screening test particularly in trauma and arthritis. Musculoskeletal ultrasound and magnetic resonance imaging are the most suitable modalities for the investigation of the rotator cuff, having high sensitivities and specificities for full-thickness tears. Musculoskeletal ultrasound and magnetic resonance imaging are less accurate in the detection of partial-thickness tears with greater observer variability. This article reviews the normal and pathologic imaging features of the rotator cuff and highlights the potential usefulness and limitations of various imaging modalities in the assessment of the tendon and the potential impact of imaging findings on clinical patient care.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.005
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.005

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 head0.071
GPT teacher head0.408
Teacher spread0.336 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations26
Published2011
Admission routes1
Has abstractyes

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