Small-molecule antivirals treatment for Covid-19: A systematic review and network meta-analysis
Bibliographic record
Abstract
Supplemental Materials for "Small-molecule antivirals treatment for Covid-19: A systematic review and network meta-analysis". Our study was registered on PROSPERO (CRD42023396617) and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. The protocol was also showed . The study characteristics about 92 RCTs and 68 retrospective studies were shown. We utilized the revised Cochrane Risk of Bias tool for RCTs and the Newcastle Ottawa Scale (NOS) for retrospective studies. A total of 92 RCTs were included, of which 42 RCTs were comprehensively evaluated as "High risk" due to allocation concealment and blinding, 15 RCTs were evaluated as "Unclear risk" due to blinding and other biases. A total of 67 retrospective studies were included, of which 34 were mainly downgraded for the typicality of the exposed study, comparability of studies on the basis of the design or analysis, and adequacy of follow up of cohorts.
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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 | 0.008 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.090 | 0.004 |
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".