59 THE BC RESEARCH CONSORTIUM OF NEURO-ONCOLOGY (RECON)
Bibliographic record
Abstract
Abstract High-grade gliomas (HGGs) are deadly primary brain tumours in pediatric and adults with the lowest survival rates in allcancer (< 10%). The Research Consortium for Neuro-oncology (ReCoN) is a team consist of clinicians and researchers in BC Cancer and Vancouver General Hospital aiming to identify disease mechanisms of poorly defined “histone H3- and IDH-WT” HGGs. The study aims to accelerate the derivation of patient-specific avatar glioma models, agnostically nominate therapeutic targets through genomics, and to empirically evaluate therapeutic efficacy/cytotoxicity using patient-derived cell models. As a proof-of-concept study, 12 primary resected grade IV glioblastoma tumour and tumour-derived cell models will undergo matched molecular profiling, including long read whole genome sequencing and single cell ATAC- and RNA-seq. Computational tools such as GRETTA will be used to nominate targetable genetic network vulnerabilities via small molecule compounds. The nominated compounds will be evaluated for efficacy/cytotoxicity using patient-derived models. Through this pilot, we aim to develop an end-to-end workflow to enhance the detection of driver mutations and design of driver-specific therapies in “WT” HGGs to improve patient-specific care.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; a candidate call from one teacher head, 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".