Development of a Biomimetic Metallic Femoral Stem: Methodological Approach
Bibliographic record
Abstract
In this communication, a new methodological approach is proposed to develop a biomimetic metallic femoral stem. The design of this stem starts with the definition of an outer skin by reproducing the shape and overall dimensions of a Stryker® femoral stem to be implanted in an artificial femur model from Sawbones®. In-house algorithms are then used to generate two types of porous structures inside the outer skin: either a stochastic cubic-based porous structure or an ordered diamond-type porous structure. Next, a model of the femur-stem assembly is developed using the finite element method. The fully dense Stryker stem replica and two porous stems are fabricated using selective laser melting technology. Then, comparative mechanical testing is carried out using the ISO 7206-4 (2010) guidelines. These tests are conducted on an intact artificial femur (reference case) and on the identical femurs, but now implanted with the fully dense and porous stems. Using digital image correlation tools, the results of four series of tests are compared to assess which implant design leads to the lowest stress shielding in the implanted femur. Finally, the experimentally measured strain fields are compared to the numerical predictions to validate the numerical models.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".