Practical considerations when providing palliative care to patients with neuroendocrine tumors in the context of routine disease management or hospice care
Bibliographic record
Abstract
This serves as a white paper by the North American Neuroendocrine Tumor Society (NANETS) on the practical considerations when providing palliative care to patients with neuroendocrine tumors in the context of routine disease management or hospice care. The authors involved in the development of this manuscript represent a multidisciplinary team of patient advocacy, palliative care, and hospice care practitioners, endocrinologist, and oncologists who performed a literature review and provided expert opinion on a series of questions often asked by our patients and patient caregivers affected by this disease. We hope this document serves as a starting point for oncologists, palliative care teams, hospice medical teams, insurers, drug manufacturers, caregivers, and patients to have a frank, well-informed discussion of what a patient needs to maximize the quality of life during a routine, disease-directed care as well as at the end-of-life.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".