Closed Reduction and Early Mobilization in Fractures of the Humeral Capitellum
Bibliographic record
Abstract
Seven consecutive patients with an isolated fracture of the humeral capitellum were treated by a single surgeon at a Level II care facility according to a simple treatment algorithm. Closed reduction was attempted in all cases using a standard technique. After reduction, the arm was splinted at 90° of flexion and mobilized at 14 days. All patients completed a clinical and radiographic follow-up consisting of a radiographic evaluation of reduction, elbow range of motion, Disabilities of the Arm, Shoulder and Hand Questionnaire, and a subjective rating of patient satisfaction. None of the patients required conversion to open reduction internal fixation or excision. Disabilities of the Arm, Shoulder and Hand Questionnaire scores ranged from 6 to 13 points (out of 100; mean, 9). The mean flexion/extension arc of motion obtained was 126° with minimal loss of rotation. Patient satisfaction was rated as excellent in five patients and good in two. All fractures appeared united at the most recent clinical and radiographic review. Closed reduction and early mobilization appears to be a safe and effective method of treating displaced fractures of the humeral capitellum with clinical results comparable to that of open reduction internal fixation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".