Gustavo Turecki: Three fundamental questions – How does the brain respond to social and emotional experiences? Why does psychological trauma trigger depressive states? What are the mechanisms of antidepressant responses?
Bibliographic record
Abstract
Gustavo Turecki MD PhD FRSC is a clinician scientist whose work focuses on understanding brain molecular changes that occur in major depressive disorder and suicide, as well as molecular processes that explain antidepressant treatment response. Dr. Turecki is Full Professor and Chair of the Department of Psychiatry at McGill University, the Scientific Director and Psychiatrist-in-Chief of the Douglas Institute in Montreal, Canada, where he also heads the Depressive Disorders Program. He has authored over 600 publications, including research articles in leading peer-reviewed journals such as Nature Neuroscience, Nature Medicine, and The Lancet and is among the world's most highly cited scientists according to Clarivate, Web of Science. He has received several national and international awards and sits on several advisory boards. Dr. Turecki graciously offers our audience a glimpse into his personal and professional journey.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.009 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.010 |
| 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".