Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
GRADE is a globally recognized approach for assessing the certainty of evidence (also: quality or certainty of evidence) and formulating recommendations in systematic reviews, guidelines and other evidence syntheses. GRADE (Grading of Recommendations Assessment, Development and Evaluation) was introduced approximately 20 years ago by an international working group led by Canadian physician Gordon Guyatt, one of the pioneers of evidence-based practice [ 1 ]. GRADE has evolved continuously over time and has now reached a high level of complexity. In the context of the strengths and weaknesses of the established GRADE concept, the Core GRADE approach recently presented by Guyatt et al. represents a significant development, which should lead to simpler and more frequent use of GRADE [ 2 ]. The new Core GRADE approach is described in detail in a 7-part series of articles and is highly relevant to physiotherapy science [ 2 ]. Publication History Article published online: 08 December 2025 © 2025. Thieme. All rights reserved. Georg Thieme Verlag KG Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it