MétaCan
Menu
Back to cohort
Record W4392912567 · doi:10.53555/sfs.v10i3.2345

Pharmacognostical And Phyto Analytical Studies On Musali Khadiradi Choornam – An Ayurvedic Formulation For The Treatment Of Uterine Disorders

2023· article· en· W4392912567 on OpenAlexvenueno aff
Akshaya. C.P, Prakash Yoganandam G

Bibliographic record

VenueJournal of Survey in Fisheries Sciences · 2023
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Medicinal Plants
Canadian institutionsnot available
Fundersnot available
KeywordsTraditional medicineAyurvedic medicineMedicine

Abstract

fetched live from OpenAlex

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. 

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.199

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.355
GPT teacher head0.432
Teacher spread0.077 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Survey in Fisheries SciencesSame topicPhytochemicals and Medicinal PlantsFrench-language works237,207