Additional file 1 of The therapeutic window of intravenous immunoglobulin (IVIG) and its correlation with clinical outcomes in Kawasaki disease: a systematic review and meta-analysis
Bibliographic record
Abstract
Supplementary appendix file: Supplementary Material, Appendix S1. Search strategies. Supplementary Material, Appendix S2. List of references with final exclusion reasons. Supplementary Material, Appendix S3. IVIG treatment protocol and definitions of IVIG resistance. Supplementary Material, Appendix S4. Newcastle-Ottawa scale to rate risk of bias for cohort and case-control study. Supplementary Material, Appendix S5. Cochrane Risk of Bias tool 2.0 (RoB 2) to rate risk of bias for randomised trials. Supplementary Material, Appendix S6. Evidence profiles. Supplementary Material, Appendix S7. Forest Plot of risk ratios (RR) for CALs during 1–2 months follow-up for Early IVIG VS Late IVIG. Supplementary Material, Appendix S8. Sensitivity analysis of initial IVIG resistance. Supplementary Material, Appendix S9. Sensitivity analysis of CALs in acute phase. Supplementary Material, Appendix S10. Subgroup analysis of initial IVIG resistance. Supplementary Material, Appendix S11. Subgroup analysis of CALs in acute phase. Supplementary Material, Appendix S12. Subgroup analysis of CAA in the acute phase for Early IVIG VS Late IVIG. Supplementary Material, Appendix S13. Subgroup analysis of CAA during 1–2 months follow-up for Early IVIG VS Late IVIG. Supplementary Material, Appendix S14. Subgroup analysis of coronary artery dilation in acute phase for Early IVIG VS Late IVIG. Supplementary Material, Appendix S15. Subgroup analysis of coronary artery dilation during 1–2 months follow-up for Early IVIG VS Late IVIG. Supplementary Material, Appendix S16. Funnel plot of initial IVIG resistance. Supplementary Material, Appendix S17. Funnel plot of CALs in acute phase.
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 | 0.004 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.749 | 0.031 |
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".