Naturopathic Oncology Modified Delphi Panel
Bibliographic record
Abstract
UNLABELLED: Naturopathic oncology is a relatively new and emerging field capable of providing professional integrative or alternative services to cancer patients. Foundational research is critical to identify topics in the clinical and research development of naturopathic oncology for future growth of the field. STUDY DESIGN: This study implements a modified Delphi protocol to develop expert consensus regarding ethics, philosophy, and research development in naturopathic oncology. METHODS: The modified protocol implements a nomination process to select a panel of 8 physicians and to assist in question formulation. The protocol includes an in-person discussion of 6 questions with multiple iterations to maintain the concept of the Delphi methodology as well as a postdiscussion consensus survey. RESULTS: The protocol identified, ranked, and established consensus for numerous themes per question. Underlying key topics include integration with conventional medicine, evidence-based medicine, patient education, patient safety, and additional training requirements for naturopathic oncologists. CONCLUSIONS: The systematic nomination and questioning of a panel of experts provides a foundational and educational resource to assist in clarification of clinical ethics, philosophy, and research development in the emerging field of naturopathic oncology.
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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 | 0.095 | 0.094 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.005 |
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".