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Record W2165796645 · doi:10.1177/147323001103900210

Evaluation of the Clinical Significance of Classification of Traumatic Anterior Shoulder Instability Using Double-Contrast Computed Tomography Arthrography

2011· article· en· W2165796645 on OpenAlexaboutno aff
YD Hao, Fang Cui, WH Zhu, LY Lu, Wang Yb

Bibliographic record

VenueJournal of International Medical Research · 2011
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineComputed tomographyMagnetic resonance imagingConservative treatmentRehabilitationRadiologyAnterior shoulderNuclear medicineSurgeryPhysical therapy

Abstract

fetched live from OpenAlex

This study evaluated the clinical significance of traumatic anterior shoulder instability (TASI) classification using double-contrast computed tomography (CT) arthrography. Patient were randomly assigned to two groups: group 1 (n = 62); and group 2 (n = 63). TASI symptom severity in group 1 was assessed using physical signs of shoulder trauma and conventional X-ray, CT and magnetic resonance imaging; these patients received either conservative management (with physical rehabilitation) or standard surgery. Group 2 underwent double-contrast CT arthrography to classify TASI; its findings formed the basis of subsequent management. At 24 months post-therapy, significant improvements in clinical outcomes were observed in group 2: Constant scores were higher and Western Ontario Shoulder Instability Index scores were lower. At 24 months, recurrence rates were 21.0% (13/62) in group 1 and 7.9% (5/63) in group 2. Findings suggested that TASI classification using double-contrast CT arthrography provided meaningful information thereby improving treatment efficacy.

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)0.014
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score0.638

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.443
GPT teacher head0.529
Teacher spread0.086 · 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 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

Citations4
Published2011
Admission routes1
Has abstractyes

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