Estimating Bone Stiffness in the Proximal Humerus using Single Energy CT and Internal Density Calibration for Stemless Shoulder Arthroplasty
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".