Supplementary Data from Determining the Optimal Adjuvant Therapy for Improving Survival in Elderly Patients with Glioblastoma: A Systematic Review and Network Meta-analysis
Bibliographic record
Abstract
Supplementary Table 1. Additional baseline characteristics of all included studies (randomized and non-randomized). Supplementary Table 2. Cochrane Collaboration tool for assessing risk of bias in randomized trials. Supplementary Table 3. Newcastle Ottawa Quality Assessment Scale for cohort studies Supplemental Table 4. Results of the network meta-analysis including RCT only split by direct and indirect evidence and assessment of consistency between direct and indirect estimates Supplemental Table 5. Results of the network meta-analysis including non-randomized trials split by direct and indirect evidence and assessment of consistency between direct and indirect estimates Supplemental Table 6. Results of the network meta-analysis including trials adjusting for MGMT methylation promoter status split by direct and indirect evidence and assessment of consistency between direct and indirect estimates Supplemental Table 7. Quantification of heterogeneity and tests of heterogeneity (within designs) and inconsistency (between designs) for secondary efficacy outcomes
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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 | 0.113 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.012 |
| Bibliometrics | 0.014 | 0.017 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.395 | 0.021 |
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".