The effect of ankle posture on the load pathway through the hindfoot
Bibliographic record
Abstract
The foot-ankle complex is frequently injured in a wide array of debilitating events such as car crashes. Numerical models and experimental tests have been used to assess injury risk, but most do not account for the variations in ankle posture that frequently occur during these events. In this study, the positions of the bones of the foot-ankle complex (particularly, the hindfoot) were quantified over a range of postures. Computed tomography scans were taken of a male cadaveric leg under axial loading with the ankle in five postures in which fractures are commonly reported. The difference in the location of the talus and calcaneus between the neutral and each repositioned posture was quantified, and substantial rotations and displacements were observed for all postures tested (talus: 3°-21.5°, 1.5-10.5 mm; calcaneus: 10°-20°, 1.5-24.5 mm). Strains were also recorded at six locations on bones of the ankle during testing and were found to be highest in the calcaneus during inversion-external rotation and highest in the talus during eversion-external rotation. Postural changes likely affect the load pathway of the foot-ankle complex, potentially altering the stress and strain fields from that of the neutral case and changing the location of fracture. This highlights the need for injury-predicting studies examining the effect of these positional changes and to develop revised injury criteria accounting for the most vulnerable conditions.
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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".