Correlation of Mock Board Examination Scores During Anatomic Pathology Residency Training with Performance on the Certifying Examination
Bibliographic record
Abstract
Mock board exams are common in residency programs across many disciplines. However, the value of mock board results in predicting success on the actual certifying examination is largely anecdotal and undocumented. The University of Tennessee anatomic pathology residency program has a long history of giving mock board exams twice a year during the course of the 3-year diagnostic training program. The mock exams give residents a sense of the types of questions that may appear on the actual certifying examination. The resulting scores serve to help identify improvement areas to focus additional study. In addition, by providing residents the mental and physical experiences designed to mimic the test day, we hope to better prepare these trainees for optimal performance on the certifying examination. This study correlated mock board results of 16 anatomic pathology residents, from July 2006 through January 2016, with their subsequent performance on the certifying exam. The results of these biannual exams were significantly correlated ( p < .001) with results for the American College of Veterinary Pathologists Certifying Examination.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".