The integration of bio-medicine and culturally based alternative medicine: implications for health care providers and patients
Bibliographic record
Abstract
Complementary and alternative medicine (CAM) are therapies used along with or in place of bio-medicine. Many forms of CAM originate in culture, referred to as culturally based alternative medicines. Usage of CAM is high with large numbers of patients using CAM for mental health, pain and musculoskeletal problems. Their desire for holistic care may be the impetus for this interest, as alternative care practitioners spend more time analyzing illness symptoms. These factors along with the global migration of immigrants accustomed to traditional medicine but now immersed in biomedical health care systems, has created potential for misunderstanding. Drug interactions for some forms of CAM taken with bio-medicine can occur. Insufficient scientific studies about CAM has reduced acceptance and educational opportunities to learn about CAM are limited. Ideas for policy and research are forming.
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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 | 0.021 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 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".