Research Productivity Among Canadian First Year Dermatology Residents: A 15 Year Analysis
Bibliographic record
Abstract
A retrospective review was conducted to obtain names of the residents that began training in Canadian dermatology residency programs between 2008 and 2022. Metrics reflective of research productivity (publication count, dermatology publications, authorship position, and H-index) were obtained from Scopus and trends were identified and evaluated using descriptive, univariate, and bivariate statistics. From the 10 Canadian residency programs, 371 dermatology residents producing 828 publications, of which 329 were dermatology-related were identified. Overall, 56% of residents had a minimum of one publication at the time of the match, with a mean of 2.23 + 4.27 publications and H-index of 1.36 + 2.23. A significant increase in all research productivity metrics was observed during the 2018 – 2022 period. Over the past 15 years, the amount of publications authored by incoming dermatology residents has increased significantly which may suggest an increased emphasis placed on medical research by medical students and residency programs.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.026 | 0.049 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".