Bibliographic record
Abstract
In societies with a free and open judiciary system, individuals are permitted to challenge a judge's verdict, ability to remain impartial, and conduct. In the first situation, a higher court of appeal typically handles the matter.1 In the second, the judge is disqualified from overseeing a case if an objective observer raises reasonable questions about the judge's impartiality.2 In the third situation, a governing body, such as a judicial council, hears the complaint. To minimize the likelihood of such events, judges are appointed based on their legal knowledge, prior experience, and a historical demonstration of impartiality and fairness. Although most medical journals and their editors conduct themselves fairly, there are some differences between their practice and that of a judiciary body. In this article, I pose four questions to medical journal editors concerning their impartiality and training as researchers and editors, and the options available to those who disagree with a decision rendered by an editor or editorial board.
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 | 0.096 | 0.317 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.012 | 0.017 |
| Scholarly communication | 0.037 | 0.017 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.014 | 0.012 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".