Bibliographic record
Abstract
Introduction Low-grade gliomas (LGG) are diffusely infiltrating primary tumors of the cerebral hemispheres, and originate from glial tissue (Kleihues & Cavanee, 2000). Patients with these tumors, like any patient with a brain disease, may experience cognitive complaints and have cognitive deficits on examination. In LGG patients, who usually have a paucity of neurological deficits, these cognitive complaints and deficits may be particularly prominent, in contrast to patients with high-grade gliomas (HGG). In HGG patients, the rapidly growing tumor typically gives rise to hemiparesis or increased intracranial pressure, which may overshadow more subtle cognitive deficits (Ashby & Shapiro, 2004; Rees, 2002). Moreover, LGG patients have a relatively good prognosis with median survival rates ranging from 5 to more than 15 years. Long-term-surviving LGG patients run the risk of late toxicity of treatment. Tumor and treatment effects may impair cognitive functioning in these patients during the course of their disease and have a deleterious impact on the quality of life of the patient and their family. Epidemiology and biology, pathology and genetics, clinical and imaging features, prognostic factors in LGG Epidemiology and biology The percentage of low-grade tumors amongst gliomas, the most common primary brain tumor, ranges between 15% and 20% (Kleihues & Cavanee, 2000). The incidence of gliomas in adults is 5 to 7 per 100 000 (Bondy & Wrensch, 1996). This figure has remained stable for many years, unlike that of other brain tumors such as primary central nervous system (CNS) lymphoma, which is increasing in incidence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.058 | 0.032 |
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".