Bibliographic record
Abstract
The method used by the working group was an iterative process based upon a structured review of the relevant literature by the four author groups. Review papers were circulated to the members of the group before the conference and formed the basis for subsequent discussions. Each paper was subject to detailed collective analysis and subsequently modified on the basis of the panel's discussions and referenced to additional relevant literature where appropriate. The group assessed the levels of evidence for the claims and statements made in the supporting documentation. It was recognized that it was often necessary to adopt a compromise between acceptance of the lowest level, resulting in the largest body of material, and the highest level, which in some cases, produced little evidence. While this approach does not represent endorsement of lower evidence levels per se, it was designed to provide conclusions of clinical utility within the existing knowledge base. The papers, following the scrutiny, were amended and approved by the expert group. The consensus report was prepared by the working group after detailed considerations of the five approved papers.
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 | 0.115 | 0.243 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.011 | 0.007 |
| Insufficient payload (model declined to judge) | 0.043 | 0.035 |
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".