49th Annual Congress of the Canadian Neurological Sciences Federation
Bibliographic record
Abstract
Dr. Dylan Blacquiere is a fellow in stroke neurology at the University of Ottawa, and has been a peer reviewer for the Canadian Journal of Neurological Sciences for the past three years.He completed his medical school at Dalhousie University in Halifax, and finished a residency in adult neurology at the University of Ottawa in 2012.His publications and research interests include palliative care and stroke, systems of stroke care, and rural-urban disparity in stroke care, as well as in knowledge translation of stroke care to the community at large.He has recently accepted a position as a stroke neurologist in Saint John, New Brunswick, and will be continuing his work there.In his spare time, he and his wife Mary enjoy camping, hiking and running, as well as being unrepentant science-fiction nerds, not necessarily in that order.We are pleased to present the 2013 CJNS Reviewer of the Year Award to Dr. Dylan Blacquiere from the University of Ottawa, Ottawa, Ontario.Dylan has provided excellent, timely reviews of numerous articles.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.274 | 0.094 |
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".