Posterior Malleolus: Morphologic Classification, Morphometry, and Clinical Insights
Bibliographic record
Abstract
Background: In this study, we provide a comprehensive description of the morphometrics of the distal tibiae and propose that the intact posterior malleolus (PM) exhibits clinically relevant morphologic variation. These differences may have implications for fracture classification, fixation strategy, and implant design. Methods: Fifty-two isolated dry tibias were analyzed to determine the PM morphometric parameters. Five key morphometric points were identified, and the PM was defined as the posterior bony projection of the distal tibial epiphysis. The malleolar groove established the PM's medial limitation, the posterior portion of the fibular notch defined the lateral limit, and the anterior boundary was a line connecting these landmarks across the inferior articular surface. PM shapes were categorized based on consistent morphologic patterns. Cross-sections of the distal tibia were performed to assess trabecular bone morphology and density. Results: We found the PM presenting 3 distinct morphologic types: rounded, triangular, and trapezoid. Triangular and trapezoid types exhibited larger dimensions and robust bone tissue, whereas tibias with a rounded PM displayed smaller dimensions and delicate bone architecture. Conclusion: These novel findings reveal PM morphologic diversity, which may enhance our understanding of PM fracture patterns and optimize the development of surgical implants.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".