Biomechanical testing of a hybrid locking plate fixation of equine sesamoid osteotomies
Bibliographic record
Abstract
OBJECTIVE: To compare the biomechanical properties of a hybrid locking compression plate (LCP) construct with the compression screw technique as a treatment for transverse mid-body proximal sesamoid bone fractures. METHODS: Ten paired forelimbs from abattoir horses were used. The medial proximal sesamoid bone of each limb was osteotomized transversely and randomly assigned, to either repair with a two-hole 3.5 mm LCP or a 4.5 mm cortical screw placed in lag fashion. Each limb was tested biomechanically by axial loading in single cycle until failure. The point of failure was evaluated from the load-displacement curves. Then a gross evaluation and radiographs were performed to identify the mode of failure. RESULTS: The loads to failure of limbs repaired with the hybrid LCP construct (4968 N ± 2167) and the limbs repaired with the screw technique (3009 N ± 1091) were significantly different (p <0.01). The most common mode of failure was through a comminuted fracture of the apical fragment of the proximal sesamoid bone. CLINICAL SIGNIFICANCE: The LCP technique has potential to achieve a better fracture stability and healing when applied to mid-body fractures of the proximal sesamoid bone. Further testing, particularly fatigue resistance is required to corroborate its potential as a treatment option for mid-body fractures of the proximal sesamoid bone.
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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".