Bibliographic record
Abstract
In this issue, we take the opportunity to thank our reviewers. It is often said that if you want something done, you need to ask a busy person. This certainly applies to our peer review process. We want expert opinions, and experts are always up to their ears in work. As I explained in the editorial published in the January issue, we will be raising the bar significantly for publication in the Canadian Journal of Psychiatry. We have sent out new guidelines to our reviewers asking them to recommend papers only when they are clearly excellent. Moreover, the Journal will concentrate on its academic mandate, accepting only empirically based studies and systematic reviews. We are not really happy about turning down other types of papers, as well as no longer publishing case reports as letters. However, our focus has to be on papers that contribute to the development of scientific psychiatry. The efforts of our reviewers, most of whom are academics, will make it possible for the Journal to increase its impact. Journal Reviewers in 2004 / Reviseurs de la Revue en 2004 Manuscript reviewers /Reviseurs de textes Donald E Addington F A Allodi Julio E Arboleda-Florez Suzanne Archie Pierre AM Beausejour Philip R Beck Mark H Ben-Aron Jacques Bernier Peter Bieling Joan E Bishop Roger C Bland Michael Bond Dominique Bourget Rudradeo C Bowen Richard Boyer Elspeth Bradley Susan J Bradley Simon A Brooks Alain Brunei Barry Campbell Corine Carlisle Nicola Casacalenda Gary Andrew Chaimowitz R Chandrasena Dara A Charney Philip N Cheifetz Pierre Chue Paul E Copus Marc Corbiere Nicholas J Coupland David Neil Crockford Jonathan S Davine John C Deadman Nicholas J Delva Ruth Ann Dickson Jacques Drouin Nady el-Guebaly Charl Els Murray W Enns Stuart Fine Sandra N Fisman William Phillip Fleisher Guillaume Galbaud du Fort David S Goldbloom Benjamin Goldstein Jean-Yves Gosselin Paul Grof Stephane Guay Francois Guillem David J Harris Lily Hechtman Kathy Hegadoren PCS Hoaken Stephen Hucker Abel Ickowicz Umesh Ravi Jain R Wade Junek Sylvia Kairouz Allan S Kaplan Edward Kingstone Laurence J Kirmayer Bill J P Komer Robert P Kraus Robert Krell Joane Labrecque Carl Lacharite Martin Lalumiere Raymond W Lam Pierre Landry J Ken Le Clair Pierre Leichner Jean-Michel Le Melledo Anthony Levinson Anthony Joseph Levitt Paul S Links John Livesley Duncan J MacCrimmon Roderick J Macleod Ashok K Malla Catherine Mancini Paul Max William O McCormick Rosemary Meier Harold Merskey Roumen Milev Klaus K Minde Rachel L Morehouse Louis Morissette Philippa Anne Moss Jean-Pierre Mottard Michael F Myers Luc Nicole RichardLO'Reilly Werner J Pankratz Joel Paris Irene Patelis-Siotis Scott Burton Patten Patricia A Pearce P Susan Penfold Emmanuel Persad Gilbert Pinard Trevor Prior Alexander Rae-Grant Quentin Rae-Grant Vivian Rakoff R. …
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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 | 0.033 | 0.322 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.017 | 0.010 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.106 | 0.124 |
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".