Bibliographic record
Abstract
Biomarkers are en vogue. Although few ever prove to be of practical value or find their place in routine clinical testing, occasionally a biomarker of great importance is identified, a biomarker that tells us something fundamental about a disease or points us to a specific therapeutic intervention. One such biomarker in neurooncology is the codeletion of chromosomal arms 1p and 19q in oligodendrogliomas, which is highly associated with classic histopathology, and as such has aided diagnosis, and, importantly, identifies a type of brain cancer that grows slowly and responds to treatment. The recent discovery of a somatic mutation in isocitrate dehydrogenase genes (IDH) in infiltrative gliomas likewise stands out, predicting a favorable clinical outcome and shedding light on the molecular pathogenesis of these neoplasms. In this issue of Neurology ®, Labussiere et al.1 make the remarkable observation that 1p and 19q allelic loss is invariably associated with IDH mutations. In a cohort of 764 gliomas, those with codeletion of chromosome 1p and 19q had mutations of either IDH1 (92%) or IDH2 (8%), whereas only one third of tumors with variable partial deletions of 1p and 19q, …
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.005 | 0.016 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.023 | 0.038 |
| Insufficient payload (model declined to judge) | 0.007 | 0.007 |
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".