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Record W2811284819 · doi:10.3329/dujps.v17i1.37125

A Comparative Analysis of Clitoria ternatea Linn. (Butterfly Pea) Flower Extract as Natural Liquid pH Indicator and Natural pH Paper

2018· article· en· W2811284819 on OpenAlexaff
Nur Faezah Syahirah L, Muhammad Umar Lutfi MY, Ayu Tarwiyah Tri Atika, Muhammad Hafiz R, Muhammad Zulhelmi OA, Mohd Ariff Adzhan O, Khor PY

Bibliographic record

VenueDhaka University Journal of Pharmaceutical Sciences · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMedicinal Plant Research
Canadian institutionsRoyal College of Physicians and Surgeons of Canada
Fundersnot available
KeywordsClitoria ternateaTitrationChemistryButterflyTraditional medicineChromatographyBiologyMedicine

Abstract

fetched live from OpenAlex

Clitoria ternatea Linn (CT) or Butterfly pea flower is a blue flower edible plant, which is commonly used as food colouring. The objective of this study was to develop a liquid and paper pH indicator from CT extracts. The effectiveness of CT extract as pH indicator was evaluated by titration and product testing result against standard indicator. The stability of CT extracts were also conducted in 7 days storage. Findings from this study shows that CT extract is an effective liquid pH indicator except for weak acid samples. Whereas pH paper made from CT extract is effective as pH paper except for testing pH range from 4 -6. It is concluded thatCT extracts can be potentially effective pH indicator.Dhaka Univ. J. Pharm. Sci. 17(1): 97-103, 2018 (June)

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.048
GPT teacher head0.352
Teacher spread0.304 · 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 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

Citations25
Published2018
Admission routes1
Has abstractyes

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