Non‐Patient‐Based Clinical Licensure Examination for Dentistry in Minnesota: Significance of Decision and Description of Process
Bibliographic record
Abstract
In recent years in the United States, there has been heightened interest in offering clinical licensure examination (CLE) alternatives to the live patient-based method in dentistry. Fueled by ethical concerns of faculty members at the University of Minnesota School of Dentistry, the state of Minnesota's Board of Dentistry approved a motion in 2009 to provide two CLE options to the school's future predoctoral graduates: a patient-based one, administered by the Central Regional Dental Testing Service, and a non-patient-based one administered by the National Dental Examining Board of Canada (NDEB). The validity of the NDEB written exam and objective structured clinical exam (OSCE) has been verified in a multi-year study. Via five-option, one-best-answer, multiple-choice questions in the written exam and extended match questions with up to 15 answer options in the station-based OSCE, competent candidates are distinguished from those who are incompetent in their didactic knowledge and clinical critical thinking and judgment across all dental disciplines. The action had the additional effects of furthering participation of Minnesota Board of Dentistry members in the University of Minnesota School of Dentistry's competency-based curriculum, of involving the school's faculty in NDEB item development workshops, and, beginning in 2018, of no longer permitting the patient-based CLE option on site. The aim of this article is to describe how this change came about and its effects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.030 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".