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Record W4410024892 · doi:10.55016/pbgrc.v1i1.81406

Estimating Bone Stiffness in the Proximal Humerus using Single Energy CT and Internal Density Calibration for Stemless Shoulder Arthroplasty

2025· article· en· W4410024892 on OpenAlexaff
Chloe Stiles

Bibliographic record

VenuePeer Beyond Graduate Research Conference · 2025
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsArthroplastyCalibrationHumerusProximal humerusStiffnessBone densityMedicineOrthodonticsRadiologySurgeryMathematicsEngineeringStructural engineeringInternal medicineOsteoporosisStatistics

Abstract

fetched live from OpenAlex

Shoulder arthroplasty is a common surgical treatment for individuals with end-stage osteoarthritis (OA) within the glenohumeral joint. New stemless humeral components require only the removal of diseased bone for fixation to the proximal humerus, thereby preserving non-diseased bone for future surgical revisions. However, current pre-operative clinical measures of bone quality fail to account for the mechanical properties of the bone in the region directly supporting the component. The purpose of this study is to determine the predictive value of proximal humerus bone stiffness in patients undergoing shoulder arthroplasty for end-stage OA with patient-specific validated computational models created from retrospective pre-operative single energy computed tomography (CT). Quantitative information from single energy CT images will be used to determine vBMD and FEM estimated stiffness values in the proximal humerus. This is a first step in predicting bone strength through patient specific CT images.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.729
Threshold uncertainty score0.503

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.189
GPT teacher head0.423
Teacher spread0.233 · 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 designOther design
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

Citations0
Published2025
Admission routes1
Has abstractyes

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