Agreement among Ayurvedic practitioners in the identification and treatment of three cases of inflammatory arthritis.
Bibliographic record
Abstract
OBJECTIVE: To conduct a preliminary investigation into the consistency of approach between three Ayurvedic medicine experts on treatments for inflammatory polyarthritis. METHODS: A convenience sample of three experienced Ayurvedic practitioners was recruited. These practitioners independently assessed three subjects with inflammatory polyarthritis for health status, treatment history, and lifestyle, conducted a physical examination, and then independently determined the treatment plan. The treatment plan was recorded on standardized collection forms. The subject examination order was randomized for each practitioner. Following completion of the assessments, a facilitated discussion among the practitioners permitted each to discuss all aspects of the recommended therapies. Proceedings were audio-taped and the content analyzed. RESULTS: All three practitioners agreed upon a unified concept of Ayurvedic disease origin, disease diagnosis, and treatment approach for each patient. Seven specific treatment groupings (i.e. modalities) emerged: diet, exercise, relaxation, analgesic, anti-inflammatory, immune-enhancing, and detoxification/cleansing. Based on the single visit, the practitioners agreed upon 17 of 21 treatment groups for the three patients. CONCLUSION: Despite Ayurvedic medicine's individualized approach, considerable agreement existed among the practitioners studied. The identified Ayurvedic treatment approaches require investigation in a controlled clinical setting.
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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 | 0.020 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".