Three-dimensional design optimisation of patient-specific femoral plates as a means of bone remodelling reduction
Bibliographic record
Abstract
Previous investigations into the optimisation of internal plates have mostly focused on the material properties of the implant. In this work, we optimise the shape, size and placement of the plate for successfully minimising bone remodelling around the implant. A design optimisation algorithm based on strain energy density criterion, combined with the finite element analysis, has been used in this study. The main optimisation goal was to reduce this change and keep it close to the conditions of an intact femur. The results suggest that the anterolateral side of the bone would be the optimum location for the plate, as for the geometry, the optimum moves towards having a thick, wide and short plate. These important results could be directly applicable to orthopaedic surgeons treating a femur fracture with internal plates. Since the optimisation algorithm remains the same for any patient, this advancement provides the surgeon with a tool to minimise the post surgery remodelling by trying to maintain the natural structure of the bone.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".