A Perspective from Ontario Tech University Industrial Research Chairs on 20 Years of Capacity Building in Health Physics and Radiation Science
Bibliographic record
Abstract
ABSTRACT: Ontario Tech University (University of Ontario Institute of Technology) is one of Canada's newest universities, having been incorporated in 2002. In 20 y, the University has increased enrollment from a few hundred students to over 10,000. The University was designed to be "market driven" and as such offered courses that had high market demand. The Faculty of Energy Systems and Nuclear Science was one of the first faculties to be established at the University, with the intent to fill a gap between personnel that were retiring out of the nuclear industry and the dearth of nuclear engineers and health physicists being educated in Canada. As such, the University established unique programs in both nuclear engineering and health physics/radiation science with strong input from industry stakeholders. This paper will discuss the evolution of the Health Physics and Radiation Science program at Ontario Tech from the teaching and capacity building perspective, and it provides insight regarding health physics and radiation science research at Ontario Tech under the industrial research chair program.
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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 | 0.024 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.021 | 0.013 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 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".