Bibliographic record
Abstract
Frédérique Bernier enseigne la littérature au cégep de Saint-Laurent.Elle a fait paraître ici et là quelques bricoles par lesquelles elle tente maladroitement, en compagnie des mots des autres, de se désentraver d'elle-même.Luc Brisson, directeur de recherche [émérite] au Centre national de la recherche scientifique (Centre Jean Pépin, UMR 8230 CNRS-ENS, Paris, France), s'est fait connaître par ses travaux sur Platon et Plotin : bibliographies, traductions et commentaires.Il a aussi publié plusieurs livres et articles sur l'histoire de la philosophie et des religions dans l'Antiquité.François Gagnon est onzièmiste de formation (M.A., traduction du Corrector sive Medicus de Burchard de Worms).On retrouve ses poèmes, essais critiques et contes dans les revues littéraires et artistiques Les Écrits, Qui vive, Zone occupée, Relations, Tangence, Cahiers Victor-Lévy Beaulieu, ainsi que dans les ouvrages collectifs L'emportement (VLB, 2012) et Terres de Trickster (Possibles éditions, 2014).En friche, il reboise les forêts laurentiennes, les rocheuses, les boréales, les pacifiques, les publiques d'une côte à l'autre et
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.106 | 0.038 |
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".