The validity, reliability, and time requirement of study model analysis using cone‐beam computed tomography–generated virtual study models
Bibliographic record
Abstract
OBJECTIVES: To investigate the validity, reliability, and time spent to perform a full orthodontic study model analysis (SMA) on cone-beam computed tomography (CBCT)-generated dental models (Anatomodels) compared with conventional plaster models and a subset of extracted premolars. SETTING AND SAMPLE POPULATION: A retrospective sample of 30 consecutive patient records with fully erupted permanent dentition, good-quality plaster study models, and CBCT scans. Twenty-two extracted premolars were available from eleven of these patients. MATERIALS AND METHODS: Five evaluators participated in the inter-rater reliability study and one evaluator for the intrarater reliability and validity studies. Agreement was assessed by ICC and cross-tabulations, while mean differences were investigated using paired-sample t-tests and repeated-measures anova. RESULTS: For all three modalities studied, intrarater reliability was excellent, inter-rater reliability was moderate to excellent, validity was poor to moderate, and performing SMA on Anatomodels took twice as long as on plaster. CONCLUSIONS: Study model analysis using CBCT-generated study models was reliable but not always valid and required more time to perform when compared with plaster models.
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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 | 0.025 | 0.118 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".