Update in the management of gastroenteropancreatic neuroendocrine tumors
Bibliographic record
Abstract
Neuroendocrine neoplasms are a diverse group of neoplasms that can occur in various areas throughout the body. Well-differentiated neuroendocrine tumors (NETs) most often arise in the gastrointestinal tract, termed gastroenteropancreatic neuroendocrine tumors (GEP-NETs). Although GEP-NETs are still uncommon, their incidence and prevalence have been steadily increasing over the past decades. The primary treatment for GEP-NETs is surgery, which offers the best chance for a cure. However, because GEP-NETs are often slow-growing and do not cause symptoms until they have spread widely, curative surgery is not always an option. Significant advances have been made in systemic and locoregional treatment options in recent years, including peptide-receptor radionuclide therapy with α and β emitters, somatostatin analogs, chemotherapy, and targeted molecular therapies.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".