Bibliographic record
Abstract
Web based submissions and reviewing are here to stay A s the kids say, moving the journal onto the world wide web has been “a trip”. Although if memory serves that phrase is meant to convey something deliriously wonderful (perhaps literally so), this voyage has been like most travels—mainly pleasure but not without its painful moments. As readers and contributors will all know by now, since May 1 all new manuscripts are handled by our web site (http://submit-ip.bmjjournals.com/) and managed by Bench>Press. For reasons beyond my comprehension this has nearly doubled the rate of new submissions. For an editor, in spite of meaning more work, that is certainly good news . . . without papers we starve and die. Much more importantly, however, and far more mysterious is the fact that so many of the new papers are of such high quality. This makes life tough for the editor, but, hey . . . why do you think …
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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.015 |
| Insufficient payload (model declined to judge) | 0.114 | 0.085 |
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".