Front Matter
Bibliographic record
Abstract
Collection Mercure du Nord/Verbatim j Du nouveau pour Verbatim !Tout en poursuivant les mêmes objectifs d'actualité et de qualité, la collection prend du volume : Verbatim grandit et grossit.Le format de la maquette passe désormais à la dimension classique, ce qui permettra aux volumes de la collection de figurer plus aisément sur les étagères des librairies.En même temps, Verbatim se transforme en Cahiers recueillant l'essentiel annuel de l'activité philosophique, sociale ou politique vivante au Québec.Techniquement parlant, de la collection de monographies Verbatim passe à la collection de collectifs.Ainsi, aux titres parus précédemment, succèderont, à partir du printemps 2017, des titres sous l'enseigne de Cahiers Verbatim, volume n, année xxxx, publiés sous forme numérique et papier (à la demande).
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.890 | 0.835 |
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; the direct Gemma label and the distilled Codex classifier 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".