Being a Leader: An Interview with a Leading Clinician-Scientist, Dr. Shawn Aaron
Bibliographic record
Abstract
Dr. Shawn Aaron is a professor of medicine, senior scientist, principal investigator at the University of Ottawa, and the Chief of the Division of Respirology at The Ottawa General Hospital. He is also the Director of the Canadian Respiratory Research Network, a Canadian Institutes of Health Research (CIHR) Emerging Research Network. Dr. Aaron’s clinical and research interests include chronic obstructive pulmonary disease (COPD), asthma, and cystic fibrosis (CF). We had the pleasure to speak with Dr. Aaron about his clinical and research experiences. He shared information about his medical, academic, and leadership roles. Finally, he also provided some advice for medical trainees in their path towards practicing medicine.
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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 | 0.021 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.010 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.008 | 0.021 |
| Insufficient payload (model declined to judge) | 0.003 | 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".