Vivre et étudier à Montréal : Des tas d'astuces pour économiser et profiter pleinement de la ville Ed. 2
Bibliographic record
Abstract
Vivre et etudier a Montreal est le guide pratique que tous les etudiants attendent depuis longtemps - il s’agit d’un ouvrage qui regorge de trucs et de conseils pour les aider a economiser et a ameliorer leur situation financiere tout en conservant une bonne qualite de vie. Les etudiants quebecois, les etudiants francais et tous les etudiants etrangers qui s’appretent a demarrer, poursuivre ou reprendre leurs etudes a Montreal, a l’universite ou au Cegep, trouveront dans le guide Vivre et etudier a Montreal des reponses a toutes leurs questions. Comment financer ses etudes et faire un budget efficace? Comment reduire les frais d’interet des prets etudiants et eviter ou minimiser les dettes? Quelles sont les astuces pour se loger et trouver un appartement a Montreal a bon prix? Comment trouver un emploi et travailler a temps partiel tout en etudiant? Comment economiser sur les frais de transport, d’alimentation, de telephone? Ou acheter des meubles et des vetements pas chers? Quelles sont les bonnes adresses pour sortir et s’amuser entre amis sans se ruiner? Bref, comment vivre a Montreal une vie etudiante riche et passionnante, sans y perdre sa chemise? Vivre et etudier a Montreal, un guide qui contient une foule de conseils utiles pour tous les etudiants a Montreal, voire pour tous les Montrealais!
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.003 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.084 | 0.010 |
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".