In-Situ Fracture Tolerance of the Metatarsals During Quasi-Static Compressive Loading of the Human Foot
Bibliographic record
Abstract
Accidental foot injuries including metatarsal fractures commonly result from compressive loading. The ability of personal protective equipment to prevent these traumatic injuries depends on the understanding of metatarsal fracture tolerance. However, the in situ fracture tolerance of the metatarsals under direct compressive loading to the foot's dorsal surface remains unexplored, even though the metatarsals are the most commonly fractured bones in the foot. The goal of this study was to quantify the in situ fracture tolerance of the metatarsals under simulated quasi-static compressive loading. Fresh-frozen cadaveric feet (n = 10) were mounted into a testing apparatus to replicate a natural stance and loaded at the midmetatarsals with a cylindrical bar to simulate a crushing-type injury. A 900 N compressive force was initially applied, followed by 225 N successive load increments. Specimens were examined using X-ray imaging between load increments to assess for the presence of metatarsal fractures. Descriptive statistics were conducted for metatarsal fracture force and deformation. Pearson correlation tests were used to quantify the correlation between fracture force with age and body mass index (BMI). The force and deformation at fracture were 1861 ± 642 N (mean ± standard deviation) and 22.6 ± 3.4 mm, respectively. Fracture force was correlated with donor BMI (r = 0.90). Every fractured specimen experienced a transverse fracture in the second metatarsal. New biomechanical data from this study further quantify the metatarsal fracture risk under compressive loading and will help to improve the development and testing of improved personal protective equipment for the foot to avoid catastrophic injury.
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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 | 0.000 | 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".