Pharmacognostical And Phyto Analytical Studies On Musali Khadiradi Choornam – An Ayurvedic Formulation For The Treatment Of Uterine Disorders
Bibliographic record
Abstract
Musali khadiradi choornam (MKC) is prescribed by Ayurvedic physicians for the treatment of menorrhagia, leucorrhea, and polycystic ovaries syndrome (PCOS). The choornam contains six herbal drugs, they are Musali (Curculigo orchioides), Khadira (Acacia catechu), Amalaki (Emblica officinalis), Jambu (Syzygium cumini), Shatavari (Asparagus racemosus), and Trikanta (Tribulus terrestris). Various studies conducted by the National Institute of Health, Government of India, reveal that the prevalence of infertility among women with PCOS ranges from 70%-80%, and 60% of women aged 25-34 are affected by PCOS. The present study aims to evaluate the under-explored Ayurvedic formulation, “Musali khadiradi choornam” on its pharmacognostic and Phyto-analytical aspects as a step towards developing Pharmacopoeial standards. The morphological and powder microscopical observation helps authenticate the raw drugs and their formulation from adulterant in the market. The phytochemical screening including GC-MS studies brings out the drug on par with modern drug in the global markets. This study might be helpful for authentication of the formulation and making it available with global standards.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".