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Record W1646523565 · doi:10.1016/j.eats.2015.03.003

Use of 3‐Dimensional Printing for Preoperative Planning in the Treatment of Recurrent Anterior Shoulder Instability

2015· article· en· W1646523565 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueArthroscopy Techniques · 2015
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsToronto East General HospitalUniversity of TorontoToronto General HospitalUniversity Health NetworkMount Sinai HospitalWomen's College Hospital
Fundersnot available
KeywordsMedicineAnterior shoulderBankart lesionLesionSurgeryInstabilityExternal rotationRadiology

Abstract

fetched live from OpenAlex

Recurrent anterior shoulder instability often results from large bony Bankart or Hill-Sachs lesions. Preoperative imaging is essential in guiding our surgical management of patients with these conditions. However, we are often limited to making an attempt to interpret a 3-dimensional (3D) structure using conventional 2-dimensional imaging. In cases in which complex anatomy or bony defects are encountered, this type of imaging is often inadequate. We used 3D printing to produce a solid 3D model of a glenohumeral joint from a young patient with recurrent anterior shoulder instability and complex Bankart and Hill-Sachs lesions. The 3D model from our patient was used in the preoperative planning stages of an arthroscopic Bankart repair and remplissage to determine the depth of the Hill-Sachs lesion and the degree of abduction and external rotation at which the Hill-Sachs lesion engaged.

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.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.141
GPT teacher head0.418
Teacher spread0.278 · 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