Minimization of Bone Removal through Optimal Humeral Implant Alignment in Total Elbow Arthroplasty
Bibliographic record
Abstract
Due to their 3D nature, many CAD B-Spline surfaces are difficult to design and edit with traditional 2D interfaces, e.g., a 2D mouse.Based on an energy minimization method or variational B-Spline technique, the paper presents the technique of using a haptic device to design B-Spline surfaces.Under complex constraints and without any pre-calculation, the variational B-Spline technique used in the system can solve virtually all practical B-Spline surfaces in a matter of milliseconds.Such results are much more efficient and powerful than previous work in the variational B-Spline field.By using a haptic interface, the system allows a user in a natural 3D environment to directly manipulate/design constraints, e.g., points and curves, and in real time, the system generates energy-minimization B-Spline surfaces in response to haptic operations.The discussed technique delivers all the performance and capacity required for using haptics to design high-quality B-Spline surfaces, and haptic-based surface operations provide a powerful method for designing B-Spline surfaces.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".