L’eau est une poubelle : Une revue de la causerie de Montréal et l’eau
Bibliographic record
Abstract
Citation: Michèle Dagenais, "L’eau est une poubelle : Une revue de la causerie de Montréal et l’eau" Bio: Michèle Dagenais est un professeur a l'Universite de Montréal Abstract: Est le fleuve Saint-Laurent une poubelle géante pour la ville de Montréal? Après la causerie sur la publication Montréal et l’eau : Une histoire environnementale, je pense que oui! Mais l’eau est aussi l’âme de la ville, et Michèle Dagenais nous informe dans sa publication que le fleuve est la raison principale de la gloire d’antan de Montréal. La causerie à l’Olivieri librairie et bistro sur le 16 mars donnée Dagenais l’occasion de parler sur l’histoire de l’eau et la ville dans une façon informelle, avec beaucoup des questions de l’animatrice Carole Vallières est du public. Il est certain que la causerie vous donnera un point de vue renouvelé sur l’eau, la ville est vous.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.013 |
| Science and technology studies | 0.017 | 0.025 |
| Scholarly communication | 0.016 | 0.009 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.030 | 0.002 |
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".