Personalized endoprostheses for the proximal humerus and scapulohumeral joint in dogs: Biomechanical study of the muscles’ contributions during locomotion
Bibliographic record
Abstract
Osteosarcoma represents one of the most common bone tumours in dogs. It commonly occurs in the proximal humerus, the most affected anatomic site. Until recently, amputation or limb-sparing surgery leading to an arthrodesis coupled with chemotherapy were the only available treatments, but they often lead to complications, reduced mobility and highly impact dog's quality of life. Prototypes of both articulated and monobloc (no mobility) patient-specific endoprostheses have been designed to spare the limb afflicted with osteosarcoma of the proximal humerus. This study focuses on the biomechanical effects of endoprostheses and shoulder muscle kinematics. For each of the endoprosthesis designs, a minimal number of muscles needed to ensure stability and a certain degree of joint movement during walking is sought. A quasi-static study based on an optimization method, the minimization of the sum of maximal muscle stresses, was carried out to assess the contribution of each muscle to the shoulder function. The identification of the most important muscles and their impact on the kinematics of the prosthetic joint lead to an improvement of the endoprosthesis design relevance and implantation feasibility.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".