EDITORIAL Open Access Canadian Journal of Kidney Health and Disease: a unique launch of a unique journal
Bibliographic record
Abstract
Usually inaugural editorials are written by the Editor-in-Chief to describe the scope and vision for the journal to potential authors and readers. This editorial is written by the Editor-in-Chief, the Deputy Editors and the Associate Editors collaboratively as a clear signal that this is a unique and different journal. We will build this journal on a set of principles which are fundamental to improving the outcomes of patients with kidney disease. To that end, we aim to be supportive, to collaborate, to integrate multiple perspectives and to be open to possibilities. Résumé Habituellement, il revient à l’éditeur en chef de rédiger l’éditorial inaugural décrivant la vision et les champs d’intérêts d’un nouveau journal. Le Journal canadien de la santé et de la maladie rénale a choisi de faire les choses autrement. En effet, cet éditorial est le fruit de la collaboration entre l’éditeur en chef et les éditeurs en chef adjoints. Ce journal s’appuie sur des principes qui seront fondamentaux pour améliorer le sort de patients atteints de maladie rénale. Pour y arriver, nous nous engageons à apporter du support aux auteurs, à collaborer, à intégrer différentes perspectives et être ouverts à des nouvelles possibilités. Editorial This inaugural virtual edition of the Canadian Journal of
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 | 0.009 | 0.069 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.017 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.044 | 0.012 |
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".