Cortical Screw Purchase in Synthetic and Human Femurs
Bibliographic record
Abstract
Biomechanical investigations of orthopedic fracture fixation constructs increasingly use analogs like the third and fourth generation composite femurs. However, no study has directly compared cortical screw purchase between these surrogates and human femurs, which was the present aim. Synthetic and human femurs had bicortical orthopedic screws (diameter=3.5 mm and length=50 mm) inserted in three locations along the anterior length. The screws were extracted to obtain pullout force, shear stress, and energy-to-pullout. The four study groups (n=6 femurs each) assessed were the fourth generation composite femur with both 16 mm and 20 mm diameter canals, the third generation composite femur with a 16 mm canal, and the human femur. For a given femur type, there was no statistical difference between the proximal, center, or distal screw sites for virtually all comparisons. The fourth generation composite femur with a 20 mm canal was closest to the human femur for the outcome measures considered. Synthetic femurs showed a range of average measures (2948.54-5286.30 N, 27.30-35.60 MPa, and 3.63-9.95 J) above that for human femurs (1645.92-3084.95 N, 17.86-24.64 MPa, and 1.82-3.27 J). Shear stress and energy-to-pullout were useful supplemental evaluators of screw purchase, since they account for material properties and screw motion. Although synthetic femurs approximated human femurs with respect to screw extraction behavior, ongoing research is required to definitively determine which type of synthetic femur most closely resembles normal, osteopenic, or osteoporotic human bone at the screw-bone interface.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".