Singapore Cancer Network (SCAN) Guidelines for Systemic Therapy of High-Grade Glioma
Bibliographic record
Abstract
INTRODUCTION: The SCAN Neuro-Oncology workgroup aimed to develop Singapore Cancer Network (SCAN) clinical practice guidelines for systemic therapy for high-grade glioma in Singapore. MATERIALS AND METHODS: The workgroup utilised a modified ADAPTE process to calibrate high quality international evidence-based clinical practice guidelines to our local setting. RESULTS: Six international guidelines were evaluated- those developed by the National Comprehensive Cancer Network (2013), the European Association for Neuro-Oncology (EANO) Task Force on Malignant Glioma (2014), the European Society of Medical Oncology (2014), the Canadian GBM Recommendations Committee (2007) and the Australian Cancer Network (2009). Recommendations on the systemic therapy of high-grade glioma were produced. CONCLUSION: These adapted guidelines form the SCAN Guidelines 2015 for systemic therapy of high-grade glioma.
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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 | 0.010 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".