Bibliographic record
Abstract
Alors qu'elle souffre des insultes que graffite méchamment Geneviève sur les murs et portes de l'école, qu'elle se trouve grosse et moche comme une saucisse, qu'elle s'évade dans la lecture du roman Jane Eyre et qu'elle apprécie tout de même sa solitude, en marchant à travers les rues de son quartier de Montréal, Hélène redoute d'avoir à passer quelques jours en classe d'immersion anglaise au camp du lac Kanawana avec le reste des élèves de sa classe. Sur place, elle fait l'objet d'autres railleries. Or, l'avant dernier soir, assise sur la galerie de sa cabane, un renard la regarde et l'approche. Suzanne hurle alors et la prévient qu'il est certainement enragé, malade et dangereux. Hélène est à nouveau repliée sur elle-même, convaincue que, comme dans son roman, un malheur se cache nécessairement derrière un bonheur naissant. Mais Géraldine vient tout changer et lui apporte la complicité de son amitié sincère. [SDM]
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.107 | 0.027 |
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".