Model organisms—the critical link between gene discovery and therapeutic intervention
Bibliographic record
Abstract
Jason graduated from the University of Toronto Medical School in 1997 followed by a pediatric residency at the Hospital for Sick Children, a fellowship in pediatric hematology/oncology at Boston Children's Hospital and post-doctoral training at the Dana-Farber Cancer Institute. He is a professor at Dalhousie University in the Departments of Pediatrics, Microbiology and Immunology and Pathology, was appointed as the director of the Clinician Investigator Program (CIP) and the Graduate Program in Medical Research at Dalhousie (2014), elected president of the Canadian Society for Clinical Investigation (CSCI) (2017) and currently serves as Associate Chair Research in the Department of Pediatrics and Interim VP Research at the IWK, and as an assistant editor of the Journal of Clinical and Investigative Medicine (CIM).
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".