Feature Story: University Medal awarded at Convocation
Bibliographic record
Abstract
Belma Kamencic and Tuan Mihn Mai are this year’s recipients of the 2015 University Medal. Kamencic received the University Medal at Convocatin June 4, for having achieved academic excellence with the highest GPA on campus this past year. “I was just sitting looking at my email,” says Belma. “The first time I read that I got the medal, I was in disbelief.” Kamencic credits her early university success to hard work, the support of her family, and good study methods. Her parents, Edita and Huse, are extremely proud of their oldest daughter. Kamencic sees her parents as role models on her path to one day becoming a future medical professional. The Kamencics, originally from Bosnia and Herzegovina, moved to Saskatoon and then Regina. Their hard work and determination paid off when Edita and Huse passed their respective Canadian qualifying exams to practice medicine in Canada.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.091 | 0.025 |
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".