An in silico comparison of a novel <scp>CORA</scp> ‐based cranial closing wedge ostectomy methodology with three other techniques
Bibliographic record
Abstract
Abstract Objective To describe a CORA‐based cranial closing wedge ostectomy methodology (CCWO CORA ) and to determine whether the CCWO CORA achieves a more accurate and precise postoperative tibial plateau angle (TPA POST ) than three previously described methods. Study design In silico study. Sample population Thirteen client‐owned dogs. Methods Computed tomography (CT) scans of six Labrador retriever, six German shepherd, six Rottweiler, and six small‐breed dog (<10 kg) tibiae, originally acquired for unrelated purposes, were used for in silico planning and execution of the CCWO CORA and previously described procedures. The TPA POST , tibial long axis shift, change in tibial length and wedge angle were recorded and a linear mixed‐effects model was used to compare differences amongst techniques. Results The median TPA POST for the CCWO CORA method was 5.00° (range: 5.00–5.00°) across a variety of tibial morphologies, whereas all other methods showed greater variability. Differences in TPA POST were evident amongst methods ( p < .001) and breeds ( p < .001). Conclusions In silico, CCWO CORA methodology always achieved the target TPA POST due to its intrinsic geometric principles. As such, CCWO CORA surgeries achieved a more accurate TPA POST than previously described CCWO techniques. Clinical significance The CCWO CORA provides clinicians with a cranial closing‐wedge ostectomy methodology with entirely predictable TPA POST .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".