The effect of root and bone visualization on perceptions of the quality of orthodontic treatment simulations
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effect of root and bone visibility on orthodontists' perceptions of the quality of treatment simulations. MATERIAL AND METHODS: An online survey was used to present orthodontists with setups generated for 10 patients in two different types of view: with and without bone and roots as modeled from a cone-beam computed tomography (CBCT) scan. The orthodontists were asked to rate the quality of the setups from poor to ideal on a 100-point visual analog scale and, if applicable, to identify features of concern that led them to giving a setup a less-than-ideal rating. RESULTS: The quality ratings were significantly lower when roots and bone were visible in the setups (P < .0001). Buccolingual inclination and periodontal concerns were selected significantly more often as reasons for a less-than-ideal rating when roots and bone were shown, whereas occlusal relationship, overjet, occlusal contacts, and arch form were selected significantly more often as reasons for a less-than-ideal rating when roots and bone were not shown. The odds of selecting periodontal concerns as a reason for a less-than-ideal setup rating were 331 times greater when roots and bones were visible than when they were not. CONCLUSIONS: Additional diagnostic information derived from CBCT scans affects orthodontists' perceptions of the overall case quality, which may influence their treatment-planning decisions.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".