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Record W2809518689 · doi:10.6000/1927-5129.2018.14.36

Review of Pharmacological Activities of Vetiveria zizanoide (Linn) Nash

2018· article· en· W2809518689 on OpenAlexvenueno aff
Saroosh Zahoor, Sammia Shahid, Urooj Fatima

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEssential Oils and Antimicrobial Activity
Canadian institutionsnot available
Fundersnot available
KeywordsPhytochemicalPerennial plantEssential oilTraditional medicineAntifungalBiologyBotanyHorticultureMedicine

Abstract

fetched live from OpenAlex

Vetiveria zizanioides (Linn) Nash is a perennial magical grass of family poaceae commonly known as Khas which is highly valued grass due to its adventitious root system. It is widely distributed in the Pakistan. It is cultivated in all provinces of Pakistan due to its great economic importance. This grass grows plain ascending up to 1200m. Mostly roots stem and leaves were used for treatment of different diseases by ancestors. Adventitious roots contain essential oil which used for multipurpose such as perfumery and in pharmacological industry. Vetiver oil contains approximately 150 compounds, including sesquiterpenoide, hydrocarbons. Phytochemical analysis of leaves shows the presence of flavonoides, saponins, tannins and phenols. Various tribes of India used this tuft grass for commercial purposes. Khas serve as broom, for cooling, roof of huts and as medicine for different diseases such as sunstroke, ulcer, fever, epilepsy and in skin diseases. In this study we summaries the magical pharmacological activities of Vetiveria zizanioides such as anti inflammatory, antibacterial, antifungal, and anti malarial, anti tubercular, anti hyperglycemic, anti hepatoprotective and antioxidant activity.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.028
GPT teacher head0.278
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations6
Published2018
Admission routes1
Has abstractyes

Explore more

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