Evaluation of the use of digital study models in postgraduate orthodontic programs in the United States and Canada
Bibliographic record
Abstract
OBJECTIVE: To investigate the extent, experience, and trends associated with digital model use, as well as the advantages of using a particular study model type (digital or plaster) in postgraduate orthodontic programs in the United States and Canada. MATERIALS AND METHODS: An electronic survey consisting of 14 questions was sent to 72 program directors or chairpersons of accredited orthodontic postgraduate programs in the United States and Canada. RESULTS: Fifty-one responded for a 71% response rate. Sixty-five percent of the schools use plaster study models compared with 35% that use digital models. The most common advantages of plaster models were a three-dimensional feel and the ability for them to be mounted on an articulator. The most common advantages of digital models were the ease of storage and retrieval, and the residents' exposure to new technology. About one third of the plaster model users reported that they wanted to switch to digital models in the future, with 12% planning to do so within 1 year. CONCLUSIONS: Based on our study, 35% of accredited orthodontic postgraduate programs in the United States and Canada are using digital study models in most cases treated in their programs, and the trend is for increased digital model use in the future.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".