Bibliographic record
Abstract
Peer review of manuscripts submitted for publication is an essential process that the nursing community, like other scientific communities, adopts to ensure the quality of publications. Such a process is intended to provide an impartial mechanism through which scholarly work is evaluated by colleagues who may be selected in recognition of their expertise in the content and/or research methods to be reviewed. Authors and end users endorse the peer-review process as a testimonial to the quality of published work. It is extremely important that we preserve the integrity of the peer-review process and practise due diligence every step of the way. To that end, editors, reviewers and authors share a common responsibility toward ensuring that peer reviews are as rigorous and meaningful as possible.
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 | 0.378 | 0.823 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.016 | 0.066 |
| Scholarly communication | 0.071 | 0.070 |
| Open science | 0.011 | 0.019 |
| Research integrity | 0.044 | 0.071 |
| Insufficient payload (model declined to judge) | 0.015 | 0.031 |
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".