Bibliographic record
Abstract
Scholarly publication in international journals depends on qualified, unbiased and available referees: (1) qualified in their ability to assume each role inherent to being a peer reviewer and in willingly and competently accepting the responsibilities that coincide with these roles; (2) unbiased in focusing on the submitted research content irrespective of their own research programs in judging the submission’s merit; and (3) available to devote time to read and understand the paper, check the accuracy and relevance of references, and write a comprehensive review commenting on the strengths and weaknesses of the manuscript, the ability of the research to be replicated, and the contribution of the work to the discipline. This study investigates the range of reviewer’s roles and responsibilities in relation to author’s own assessment as a frequent reviewer for fourteen journals representing five publishing houses—and as an active researcher—in comparison with a 2019 comprehensive study of the views of 224 authors on peer review. Based on this investigation, advice will be provided to potential reviewers regarding what is expected of them in undertaking their work. Recommendations will be offered for peer review to mitigate weaknesses in the process and increase the pool of qualified peer reviewers.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Evaluation · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | medium |
| gpt | Metaresearch Domain: Evaluation · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Not applicable | medium |
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 | 0.175 | 0.469 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.006 |
| Science and technology studies | 0.015 | 0.008 |
| Scholarly communication | 0.029 | 0.011 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".