Agreement of the clinician's choice of archwire selection on conventional and virtual models
Bibliographic record
Abstract
OBJECTIVES: To compare archwire selection on dental casts with archwire selection using a three-dimensional (3D) software program (OrthoAid) and assess agreement between clinicians. MATERIALS AND METHODS: The best-fitting archwires were selected for dental casts of 100 patients with malocclusion using two approaches by three orthodontists. The first method was to visually determine the fitness of five preformed nickel titanium archwires to the arch form on a dental cast (subjective method). The second method was archwire selection on a virtual image of the same cast by means of 3D software (objective method). Agreement between selections performed by the orthodontists was calculated using Kappa statistics. The accuracy of fit of the archwires to the curves fitted to the arch form was also calculated or reversely assessed by means of the root mean square (RMS) for both methods using the Dahlberg formula. RESULTS: The mean RMS of the distances between the patient arch forms and the archwires for the subjective method was 1.163-1.366 mm. The agreement of selections between orthodontists was 42%-58% (Kappa ranged from .074 to .382). Using the 3D software (objective method), the mean RMS decreased to 0.966-1.171 mm, and agreement increased to 47% to 84% (Kappa ranged from .444 to .747). CONCLUSIONS: The use of 3D computer software for archwire selection in patients with malocclusion provided better adaptation and interexaminer reliability.
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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 | 0.000 |
| 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".