Bibliographic record
Abstract
Although there is no page limit on initial (i.e., fi rst-round) submissions, authors should strive to keep their papers at no longer than 38 pages double-spaced in a size 11 font.The page limit on the fi nal version is 38 pages.The departmental editors can relax the page limit in exceptional cases.In addition, some of the proofs, lemmas, tables and other supporting material may be included in an online companion.There is no page limit for the online companion.A page limit is imposed because papers should focus on their main contribution and short papers are more likely to be read and cited. Spacing and FormattingThe manuscript, including the abstract and references, should be double-spaced in size 11 font, and it should have one-inch margins on all four sides of the page.Each page of the manuscript should be numbered.The fi rst page of the manuscript should include the title of the paper and an abstract of 100-250 words.The title should be concise and descriptive, not exceeding 12 words.The abstract is a mini paper, and it should summarize important contents of the paper.It is not a roadmap of the paper, and it should not contain formulas, references, or abbreviations.Please list up to four key words at the end of the abstract.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.900 | 0.868 |
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".