Programme pour le colloque de Montréal "Nouvelles aventures du chapitre : division narrative et histoire des supports"
Bibliographic record
Abstract
Jeudi 2 novembre Carrefour des arts et des sciences, Salle C-3061 9h30 : Mot de bienvenue (Faculté des arts et des sciences). 9h40 : Ouverture du colloque Ugo Dionne (Université de Montréal) et Aude Leblond (Université Paris 3 – Sorbonne nouvelle). Séance 1 : « Aventures médiévales » Présidence : Richard Saint-Gelais 10h00 : Francis Gingras (Université de Montréal), « Le choc des capitulations : la disposition des Bibles en français au Moyen Âge ». 10h40 : Patrick Moran (Université Paul-Vali...
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.001 | 0.011 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; both teacher heads agree on what is shown here.
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".