Correlation Between Weber Classification of Ankle Fractures and Medial Clear Space Widening on Radiography
Bibliographic record
Abstract
Background/Objective: There is a growing interest in deltoid ligament injury and repair. The integrity of the deltoid ligament is indirectly assessed through medial clear space widening. The objective of this study was to quantify the degree of medial clear space widening in Weber A, B, and C ankle fractures. Methods: Weber A, B, and C ankle fracture radiographs were retrospectively evaluated for the medial, lateral, and superior clear spaces and data gathered on associated injuries to the medial and posterior malleoli. Multivariable regression analysis was performed with the goal of assessing whether there were significant differences among the Weber fracture types for medial, lateral, and superior clear space widening. Results: A total of 473 radiographs with lateral malleolar fractures were retrospectively evaluated with 127 being Weber A, 216 Weber B, and 130 Weber C, with an additional 89 with associated fracture of the medial malleolus and 62 of the posterior malleolus. The mean medial clear space for Weber A fractures was 3.3 ± 1.1 mm, Weber B fractures 4.3 ± 2.4 mm, and Weber C fractures 5.7 ± 3.6 mm. Weber C fractures demonstrated significantly greater medial and lateral clear space distances than Weber A or B fractures. Additional fractures of the medial or posterior malleoli were also associated with greater medial and lateral clear space distances. Conclusions: Medial clear space is significantly increased in Weber C fractures and when additional medial or posterior malleolar fractures also occur. This sheds light on the biomechanics of ankle fractures and their impact on the medial ligamentous instability.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".