The McMaster Internal Medicine Royal College Review Course: Descriptions of a Novel Program and a Survey of Participants
Bibliographic record
Abstract
Background Certification exams are the final hurdle residents overcome to complete training. Despite their high-stakes nature there are few dedicated preparation resources. In response, we created the McMaster Internal Medicine Royal College Review Course and administered a survey to participants to assess the design of the course and its perceived value. Methods The course was offered as three-hour lectures hosted every one to two weeks for a total of 15 sessions. Each session was dedicated to a specific subspecialty. Following completion of the exam, we distributed a survey to participating residents. Three iterations of this course were studied between 2018-2021. Results 112/139 residents completed the survey. 92.8% of participants found the course valuable and 70.6% felt it helped to reduce exam anxiety. Most participants (78.6%) engaged with the course during the presentations and used the resources for review during independent study. Conclusion This review course presents a valuable exam preparation resource for residents. This survey demonstrated a desire for the course to continue and may present an opportunity for other residency programs to offer similar courses.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".