Graduate programs in biophotonics: unique transdisciplinary training in applied photonics for the life sciences
Bibliographic record
Abstract
In 2008, Université Laval launched the first and only graduate programs in biophotonics in Canada. This initiative is dedicated to the training of a new generation of highly qualified researchers at the interface of life sciences and optics. It also stemmed from the strong expertise of the University in optics/photonics, its major investments in state-of-the art biophotonics infrastructure and technologies, and its desire to promote multidisciplinary training of graduate students. The programs are hosted by the Faculty of Science and Engineering in collaboration with the Faculty of Medicine, regrouping professors from 3 Faculties and 10 departments at Université Laval. The biophotonics graduate programs offer students from a wide variety of scientific backgrounds the opportunity to train in highly skilled research teams on projects that bridge the gap between traditional research fields. They benefit from transdisciplinary training opportunities in the fields of physics, chemistry, biology, biochemistry, neurosciences, medicine, engineering and ethics.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.031 | 0.013 |
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".