Bibliographic record
Abstract
INTRODUCTION Without a doubt, peer review is the measuring stick by which science is judged. Peer review is a longstanding tradition in academic circles as the standard practice for evaluating articles for publication, grants and academic promotions. The term itself conjures up certain connotations and mixed emotions. Knowing that a body of work has successfully gone through peer review immediately increases credibility and, although academics would be hesitant to confess, it is too frequently unquestioned. A recent article by John Bohannon in Science tells the story of how his bogus paper full of glaring fatal flaws was accepted by an astonishing 157 out of 255 open-access “peer reviewed” journals [1], casting doubt on the level of scrutiny from journals claiming to perform peer review. Perhaps it is time to cast aside our blind faith and understand the limitations of peer review.
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 | 0.386 | 0.631 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.007 | 0.075 |
| Scholarly communication | 0.018 | 0.022 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.022 | 0.030 |
| Insufficient payload (model declined to judge) | 0.008 | 0.007 |
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".