Evaluation and Management of Carpal Fractures Other Than the Scaphoid
Bibliographic record
Abstract
Fractures of the carpus can be debilitating injuries and often lead to chronic pain and dysfunction when not properly treated. Although scaphoid fractures are more common, fractures of the other carpal bones account for nearly half of all injuries of the carpus. Often missed on initial presentation, a focused physical examination with imaging tailored to the suspected injury is needed to identify these fractures. In addition to plain radiographs, advanced imaging such as CT and MRI are helpful in diagnosis and management. Treatment of carpal fractures is based on the degree of displacement, stability of the fracture, and associated injuries. Those that require surgical fixation often affect the congruency of the articular surfaces, are unstable, are at risk for symptomatic nonunion, are associated with notable ligamentous injury, or are causing nerve or tendon entrapment. Surgical strategies involve percutaneous Kirschner wires, external fixation, screws and/or plates, excision, or fusion for salvage. Owing to the intimate articulations in the hand, small size of the carpal bones, and complex vascular supply, carpal fracture complications include symptomatic nonunion, osteonecrosis, and posttraumatic arthritis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".