Bibliographic record
Abstract
Introduction After more than 30 years of intensive clinical and laboratory research, high-grade gliomas (HGG) [glioblastoma multiforme (GBM), anaplastic astrocytoma (AAs), anaplastic oligodendroglioma, and anaplastic mixed glioma] retain a well-deserved reputation for poor response to therapy, rapid tumor recurrence, and short overall survival. Currently available treatments, including surgery, cranial irradiation, and chemotherapy, extend survival measurably, but are almost always non-curative, and are associated with substantial toxicity. In this context, maintaining good quality of life has assumed an increasingly prominent role in selecting treatments and in designing clinical trials (Report of the Brain Tumor Progress Review Group, 2005; Taphoorn et al ., 2005), and the paradigm of compressing morbidity and “rectangularizing” the survival curve (Fries, 1980) is increasingly seen as the central goal of cancer therapy (Figure 11.1). Traditionally, myelosuppression and its attendant problems have been the dose-limiting and most important toxicities of radiation and chemotherapy. In the late 1990s and early 2000s, however, the availability of colony stimulating factors, and dramatic improvements in transfusion medicine, antibiotic therapy, and supportive care made the bone marrow more robust. Today, a strong case can be made that the nervous system has replaced the bone marrow as the most important dose-limiting end organ for cancer therapy in general, and for therapy directed at central nervous system tumors in particular. For the large number of children (Bhat et al ., 2005; Lannering et al ., 1990; Packer et al ., 2003) and for the still small but growing number of adult long-term survivors of malignant primary brain tumors, the nervous system rather than the hematopoietic system more frequently affects the quality of survival and the economic productivity of survivors.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.047 | 0.034 |
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".