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Record W2972773739 · doi:10.32622/ijrat.742019202

Phytochemical Screening of Murraya koenigii (L.) Spreng

2019· article· en· W2972773739 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Research in Advent Technology · 2019
Typearticle
Languageen
FieldMedicine
TopicMorinda citrifolia extract uses
Canadian institutionsImpact
Fundersnot available
KeywordsMurrayaPhytochemicalTraditional medicineChemistryMedicine

Abstract

fetched live from OpenAlex

Murraya koenigii (L.) Spreng., commonly known as curry leaf tree is well known in Ayurvedic medicinal system for its varied pharmacological activities like anticancer activity, antioxidant activity, anti-inflammatory activity, anthelmintic activity, antidiabetic and antimicrobial activity. The leaves of this tree had been commonly used to enhance the flavour in culinary purposes for its specific taste and aroma. It's Stem part is commonly used as datun for oral health care purposes.The secondary metabolites present in the plant are also known for its different pharmacological activities. The present study focuses on preliminary qualitative phytochemical Screening and analysis from the hydroalcoholic extracts of root, stem and leaves part which detected the presence of alkaloids, phenols, flavonoids, terpenoids, steroids and tannins in the prepared hydroalcoholic extracts using Soxhlet extraction method.

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.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.515
Threshold uncertainty score0.595

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.056
GPT teacher head0.447
Teacher spread0.391 · 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