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Record W4394774875 · doi:10.53555/sfs.v10i3.2522

Pharmacognostic And Biological Evaluation Of The Extract Of Artemisia Apiacea

2023· article· en· W4394774875 on OpenAlexvenueno aff
Ms. Himanshi Chaudhary, Mr. Navneet Kumar, Ms. Mansi Gupta

Bibliographic record

VenueJournal of Survey in Fisheries Sciences · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEssential Oils and Antimicrobial Activity
Canadian institutionsnot available
Fundersnot available
KeywordsArtemisiaTraditional medicineMedicine

Abstract

fetched live from OpenAlex

Artemisia apiacea, normally known as Apiaceae mugwort, is a conventional restorative plant with a rich history of helpful use in different customary medication frameworks. This study is intended to give a thorough pharmacognostic and organic assessment of the concentrate obtained from Artemisia apiacea. Pharmacognostical investigation, including naturally visible and infinitesimal assessment, physicochemical boundaries, and fundamental phytochemical screening, was used to lay out the quality boundaries of the plant material. Moreover, natural assessments were performed to survey the possible pharmacological effects of the concentrate, including cell reinforcement, antimicrobial, mitigating, and cytotoxic properties. The discoveries of this study give significant bits of knowledge into the pharmacological potential and quality boundaries of Artemisia apiacea separate, which could add to its usage in drug and nutraceutical ventures.   Keywords: , , , , , , . 

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)0.005
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 score0.365
Threshold uncertainty score0.190

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.333
GPT teacher head0.316
Teacher spread0.017 · 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

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