MétaCan
Menu
Back to cohort
Record W4284884550 · doi:10.47957/ijpda.v10i2.502

Evaluation of phytochemical, physicochemical and biochemical analysis of saaranai ver chooranam (the root of Trianthema decandra linn,)-a Siddha herbal medicine

2022· article· en· W4284884550 on OpenAlexfundno aff
S Heamavathi, J Kumar, S Shankar, Saravanadevi M.D, V Velpandian

Bibliographic record

VenueInternational Journal of Pharmaceutics and Drug Analysis · 2022
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Medicinal Plants
Canadian institutionsnot available
FundersMinistry of Ayurveda, Yoga and Naturopathy, Unani, Siddha and HomoeopathyWatershed Watch Salmon SocietyWorld Health Organization
KeywordsSiddhaTraditional medicinePhytochemicalMedicineHerbBiologyMedicinal herbs

Abstract

fetched live from OpenAlex

Abundant herbal remedies separately or in combination have been recommended in various medical treatises for the remedy of different diseases, Trianthema decandra Linn, (Family: Aizoaceae) familiarly known as Vellai Saaranai (Tamil) and Punarnavi (Sanskrit) is a procumbent herb widespread in the tropical and subtropical regions of the world, and also found abundantly in India. It has been widely known in different system of traditional medicines, used efficiently in Siddha for the treatment of diseases and ailments of human beings. The current study aims to endow up-to date standardized data of Saaranai ver chooranam (SVC) indicated for Gunmam with distinct observations such as physicochemical, phytochemical, biochemical, HPTLC, analysis of heavy metal, microbial load, specific pathogen, pesticide residue, aflatoxin parameters were evaluated as per PLIM guidelines, gathered and orchestrated in a prompt manner on this paper, to explore and inspire further ethno-botanical and ethno-pharmacological research and investigations towards drug discovery.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.264
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
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 head0.043
GPT teacher head0.393
Teacher spread0.350 · 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 designBench or experimental
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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Pharmaceutics and Drug AnalysisSame topicPhytochemicals and Medicinal PlantsFrench-language works237,207