Treatment Options for Pancreatic Neuroendocrine Tumors
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
The management of pancreatic neuroendocrine tumors (PanNETs) involves classification into non-functional or functional PanNET, and as localized or metastatic PanNET. In addition, while most PanNETs are sporadic, these endocrine neoplasms can also be manifestations of genetic syndromes. All these factors may assist in forming a risk stratification system permitting a tailored management approach. Most PanNETs are classified as non-functional because they are not associated with clinical sequelae of hormone excess. They are characterized by non-specific symptoms, such as abdominal pain or weight loss, resulting from mass effect related to the pancreatic tumor or secondary to distant metastases. Accurate staging of the disease is essential for determining the appropriate approach to therapy. As cure is only potentially possible with surgical resection of the tumor, it is recommended to remove all localized and limited metastatic disease. However, many patients present with metastatic and/or advanced local disease. In such instances, the goal of therapy is to control tumor growth and/or decrease tumor burden, lengthen survival, and palliate local symptoms and those of hormone excess. This typically requires a multimodal approach, including surgery, liver-directed treatment, and systemic medical therapy.
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.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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