A comparison of conventional compression plates and locking compression plates using cantilever bending in an ilial fracture model
Bibliographic record
Abstract
OBJECTIVES: The purpose of this study was to compare the stiffness, yield load, ultimate load at failure, displacement at failure, and mode of failure in cantilever bending of locking compression plates (LCP) and dynamic compression plates (DCP) in an acute failure ilial fracture model. Our hypothesis was that the LCP would be superior to the DCP for all of these biomechanical properties. METHODS: Ten pelves were harvested from healthy dogs euthanatized for reasons unrelated to this study and divided into two groups. A transverse osteotomy was performed and stabilized with either a 6-hole DCP applied in compression or a 6-hole LCP. Pelves were tested in cantilever bending at 20 mm/min to failure and construct stiffness, yield load, ultimate load at failure, displacement at failure, and mode of failure were compared. RESULTS: The mean stiffness of DCP constructs (193 N/mm [95% CI 121 - 264]) and of LCP constructs (224 N/mm [95% CI 152 - 295]) was not significantly different. Mean yield load of DCP constructs (900 N [95% CI 649 -1151]) and of LCP constructs (984 N [95% CI 733 -1235]) was not significantly different. No significant differences were found between the DCP and LCP constructs with respect to mode of failure, displacement at failure, or ultimate load at failure. CLINICAL SIGNIFICANCE: Our study did not demonstrate any differences between DCP and LCP construct performance in acute failure testing in vitro.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".