Proceedings of the Strategy Meeting for the Development of an International Consortium for Chinese Medicine and Cancer
Bibliographic record
Abstract
On November 3, 2014, in Bethesda, MD, the Office of Cancer Complementary and Alternative Medicine of the National Cancer Institute held a meeting to examine the potential utility and feasibility of establishing an international consortium for Chinese medicine and cancer. There is significant interest in the West in using components of Chinese medicine (CM) -such as botanicals and herbal medicines, acupuncture and acupressure, and qigong-in the field of oncology, as potential anticancer agents, for symptom management, and to improve quality of life. The proposal for a consortium on CM came from the Chinese Academy of Chinese Medical Sciences, with the aims of improving scientific communications and collaborations and modernizing the studies of CM for cancer. The US National Cancer Institute's Office of Cancer Complementary and Alternative Medicine agreed to work with Chinese Academy of Chinese Medical Sciences to explore the feasibility of establishing an international consortium for Chinese medicine and cancer. At the meeting, participants from the United States, China, Canada, Australia, and Korea discussed issues in CM and cancer research, treatment, and management, including potential mechanisms of action, proof of efficacy, adverse effects, regulatory issues, and the need for improving the quality of randomized clinical trials of CM treatments and supportive care interventions. Presented in these proceedings are some of the main issues and opportunities discussed by workshop participants.
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 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 | 0.021 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.015 | 0.017 |
| Insufficient payload (model declined to judge) | 0.031 | 0.006 |
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".