Development and Duration of Radiographic Signs of Bone Healing in Children
Bibliographic record
Abstract
OBJECTIVE: Few articles report the evaluation of pediatric fracture healing and dating based on radiographic appearance. We established a timetable for expected radiographic changes visible during bone healing in otherwise healthy children. MATERIALS AND METHODS: We examined 707 radiographs of fractured forearms in 141 patients. Each fracture was assessed by a pediatric radiologist who was unaware of the timing of the initial injury. Assessment included the following features: fracture margins, fracture gap, periosteal reaction, callus, bridging, and remodeling. The time interval between injury and the appearance of the radiographic features and the duration of radiographic signs were determined and correlated with age, sex, angulation, displacement, and location. RESULTS: Sclerosis at the fracture margins was evident in 85% of fractures 5 weeks after injury. Widening of the fracture gap was observed in 62% of fractures at 6 weeks. Periosteal reaction was evident on all images by 4 weeks, and after 7 weeks, periosteal reaction was separable from cortex in only 10% of fractures. Fracture callus had a density equal to or greater than that of adjacent cortex 10 weeks after injury in 90% of fractures. CONCLUSION: A wide variation exists in the appearance and duration of the radiographic signs of bone healing. Marginal sclerosis should be an expected radiographic sign of normal bone healing. Applying maximum and minimum time spans to objective radiographic signs may aid in fracture dating.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".