Core GRADE 6: presenting the evidence in summary of findings tables
Bibliographic record
Abstract
This sixth article in a seven part series presents the Core GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach to summary of findings tables. These tables provide essential information about the effects of interventions on patient important outcomes, including relative and absolute effects, certainty of evidence, and a plain language summary. For binary outcomes calculating absolute effects requires applying relative risk estimates to baseline risks from studies representative of the target population. For groups of patients with very different baseline risks, summary of findings tables include separate rows with different estimates of absolute effects. For continuous outcomes, challenges arise when individual studies use different instruments to measure patient reported outcomes. Facilitating interpretation then requires providing details about units of measurement and minimally important differences.
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 | 0.080 | 0.438 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.015 |
| Bibliometrics | 0.024 | 0.016 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.008 | 0.006 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.068 | 0.019 |
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".