Assessing evidence in public health: the added value of GRADE
Bibliographic record
Abstract
Akl EA, 2012, BMC PUBLIC HEALTH, V12, DOI 10.1186-1471-2458-12-386; Barbui C, 2010, PLOS MED, V7, DOI 10.1371-journal.pmed.1000322; Deeks JJ, 2003, HEALTH TECHNOL ASSES, V7, p[iii, 1]; Duclos P, 2012, VACCINE, V31, P12, DOI 10.1016-j.vaccine.2012.02.041; Durrheim DN, 2010, J EPIDEMIOL COMMUN H, V64, P387, DOI 10.1136-jech.2009.103226; European Centre for Disease Prevention and Control (ECDC), 2011, EV BAS METH PUBL HLT; Guyatt GH, 2011, J CLIN EPIDEMIOL, V64, P380, DOI 10.1016-j.jclinepi.2010.09.011; Guyatt GH, 2011, J CLIN EPIDEMIOL, V64, P1283, DOI 10.1016-j.jclinepi.2011.01.012; Rehfuess EA, 2011, J EPIDEMIOL COMMUN H, V65, P559, DOI 10.1136-jech.2010.130013; Schunemann H, 2010, J EPIDEMIOL COMMUNIT, V65; Sun X, 2010, BRIT MED J, V340, DOI 10.1136-bmj.c117; Sun X, 2012, BRIT MED J, V344, DOI 10.1136-bmj.e1553; WHO, GUID DEV EV BAS VACC
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How this classification was reachedexpand
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 | 0.155 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.007 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads 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".