Note from the Editors
Bibliographic record
Abstract
This 68th volume marks a number of big changes with the journal.Most notably, the editorial team has not only completely changed, but also doubled!The team is now made up of two editors, Nicole Rosen and Anne-José Villeneuve, and two co-editors, Gabriela Alboiu and Michael Dow.The new editorial assistant is Ana-Maria Jerca, and our LaTeX assistant is Radu Craioveanu.We will continue to publish the same number of pages and cutting-edge articles, but after discussions with the outgoing team, the Book Review section will be sunsetted.We will publish all book reviews that are already in the system, but we will not be soliciting or accepting any new ones, and Volume 68 will be the last volume containing book reviews.The journal also has a fresh new look, an initiative spearheaded by our previous team, but which they never got to enjoy.We will enjoy it for them, and thank them for brightening the new cover and logo!Other changes will be less obvious: while the journal has traditionally published regular-length articles, book reviews, and squibs, and has recently launched the rubric Commentaires, going forward, submissions will be referred to simply as 'long (regular) articles' and 'short articles'.The regular articles remain unchanged, but the 'short' articles will be an umbrella category covering squibs, commentaires, or other shorter contributions of interest to our readership.We hope that this flexibility will encourage the submission of a greater variety of manuscripts from a more wideranging authorship.We wish to heartily thank the outgoing team: Heather Newell, Dan Siddiqi and Máire Noonan, as well as Elizabeth Cowper, who have all helped with this transition
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 | 0.004 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.091 | 0.079 |
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".