Biomechanical Measurements of Torsion-Tension Coupling in Human Cadaveric Femurs
Bibliographic record
Abstract
The mechanical behavior of human femurs has been described in the literature with regard to torsion and tension but only as independent measurements. However, in this study, human femurs were subjected to torsion to determine if a simultaneous axial tensile load was generated. Fresh frozen human femurs (n=25) were harvested and stripped of soft tissue. Each femur was mounted rigidly in a specially designed test jig and remained at a fixed axial length during all experiments. Femurs were subjected to external and internal rotation applied at a constant angulation rate of 0.1 deg/s to a maximum torque of 12 N m. Applied torque and generated axial tension were monitored simultaneously. Outcome measurements were extracted from torsion-versus-tension graphs. There was a strong relationship between applied torsion and the resulting tension for external rotation tests (torsion/tension ratio=551.7±283.8 mm, R(2)=0.83±0.20, n=25), internal rotation tests (torsion/tension ratio=495.3±233.1 mm, R(2)=0.87±0.17, n=24), left femurs (torsion/tension ratio=542.2±262.4 mm, R(2)=0.88±0.13, n=24), and right femurs (torsion/tension ratio=506.7±260.0 mm, R(2)=0.82±0.22, n=25). No statistically significant differences were found for external versus internal rotation groups or for left versus right femurs when comparing torsion/tension ratios (p=0.85) or R(2) values (p=0.54). A strongly coupled linear relationship between torsion and tension for human femurs was exhibited. This suggests an interplay between these two factors during activities of daily living and injury processes.
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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) | 0.000 | 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".