<i>In vivo</i>micro-CT analysis of bone remodeling in a rat calvarial defect model
Bibliographic record
Abstract
The rodent calvarial defect model is commonly used to investigate bone regeneration and wound healing. This study presents a micro-computed tomography (micro-CT) methodology for measuring the bone mineral content (BMC) in a rat calvarial defect and validates it by estimating its precision error. Two defect models were implemented. A single 6 mm diameter defect was created in 20 rats, which were imaged in vivo for longitudinal experiments. Three 5 mm diameter defects were created in three additional rats, which were repeatedly imaged ex vivo to determine precision. Four control rats and four rats treated with bone morphogenetic protein were imaged at 3, 6, 9 and 12 weeks post-surgery. Scan parameters were 80 kVp, 0.45 mA and 180 mAs. Images were reconstructed with an isotropic resolution of 45 microm. At 6 weeks, the BMC in control animals (4.37 +/- 0.66 mg) was significantly lower (p < 0.05) than that in treated rats (11.29 +/- 1.01 mg). Linear regression between the BMC and bone fractional area, from 20 rats, showed a strong correlation (r(2) = 0.70, p < 0.0001), indicating that the BMC can be used, in place of previous destructive analysis techniques, to characterize bone growth. The high precision (2.5%) of the micro-CT methodology indicates its utility in detecting small BMC changes in animals.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".