Bibliographic record
Abstract
REMERCIEMENTSJe tiens d'abord remercier mon directeur de recherche, le professeur Jean-Yves Trpanier, qui a su m'encourager et me fournir une atmosphre de travail stimulante au sein de sa chaire de recherche.Je souhaite galement le remercier de m'avoir laiss une trs grande libert et de m'avoir permis de participer des confrences et des cours trs enrichissants.Je dsire aussi souligner l'aide apporte par Christophe Tribes, associ de recherche, qui m'a fourni de nombreux prcieux conseils qui m'ont aid lors de l'laboration de mon projet.Son sens de l'coute et d'ouverture ont t trs apprcis.Je souhaite galement remercier Franois Brophy ainsi que Tim Piercey de chez Pratt & Whitney Canada pour le temps et soutien qu'ils m'ont accords tout au long de mon projet.Leur exprience technique m'a permis de beaucoup apprendre et de rester les pieds sur terre.Merci aussi aux tudiants de la chaire que j'ai ctoys durant mon passage la Polytechnique pour leur camaraderie.Un merci spcial Alexandre Lupien et Benoit Malouin pour les belles parties de Ultimate Frisbee et de golf joues ensemble.Je tiens aussi remercier Mathias Emeneth ainsi que le personnel chez
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".