Brain Stem Gliomas: A Classification System Based on Magnetic Resonance Imaging
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
MR scans of 87 pediatric patients with brain stem gliomas were retrospectively reviewed to develop a new classification scheme based on MR imaging. The scheme that has been developed utilizes primarily T2-weighted images, as these most accurately show tumor extent. Tumors are characterized as to location of origin, focality, direction and extent of tumor growth, degree of brain stem enlargement, degree of exophytic growth, and presence or absence of cysts, necrosis, hemorrhage, and hydrocephalus. The use of this classification allowed identification of differences in a population of patients who were selected to be as similar as possible. This system will aid in the assessment of new protocols for treatment of brain stem tumors.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it