The molecular biology of medulloblastoma metastasis
Bibliographic record
Abstract
Medulloblastoma (MB) is the most common primary malignant brain tumor of childhood and a significant contributor to pediatric morbidity and death. While metastatic dissemination is the predominant cause of morbidity and mortality for patients with this disease, most research efforts and clinical trials to date have focused on the primary tumor; this is due mostly to the paucity of metastatic tumor samples and lack of robust mouse models of MB dissemination. Most current insights into the molecular drivers of metastasis have been derived from comparative molecular studies of metastatic and non-metastatic primary tumors. However, small studies on matched primary and metastatic tissues and recently developed mouse models of dissemination have begun to uncover the molecular biology of MB metastasis more directly. With respect to anatomical routes of dissemination, a hematogenous route for MB metastasis has recently been demonstrated, opening new avenues of investigation. The tumor micro-environment of the primary and metastatic niches has also been increasingly scrutinized in recent years, and further investigation of these tumor compartments is likely to result in a better understanding of the molecular mediators of MB colonization and growth in metastatic compartments.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".