Discussing Oncology Massage Research: an Interview with Danielle Gentile, PhD
Bibliographic record
Abstract
's readers to a new massage therapy researcher, Danielle Gentile, PhD, who is a Health Services Researcher and Assistant Professor of Medicine in the Department of Supportive Oncology at the Levine Cancer Institute for Atrium Health in Charlotte, North Carolina. Dr. Gentile's research focuses on social media in health care, integrative oncology, and the effects of integrative modalities-including massage therapy-on pain in patients with cancer. In the interview, Dr. Gentile describes what excites her about the field of massage therapy and how she integrates massage therapists into her research.
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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 | 0.017 | 0.076 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.018 | 0.026 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".