Evidence map›Paper›PMID 39468319›Full record

ArticleScientific reports2024

Machine learning-aided enhancement of white tea extraction efficiency using hybridized GMDH models in microwave-assisted extraction.

Mostafa Khajeh, Mansour Ghaffari-Moghaddam, Jamshid Piri, Afsaneh Barkhordar, Turan Ozturk

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Mostafa KhajehDepartment of Chemistry, Faculty of Science, University of Zabol, Zabol, Iran.
Mansour Ghaffari-MoghaddamDepartment of Chemistry, Faculty of Science, University of Zabol, Zabol, Iran. mansghaffari@uoz.ac.ir.
Jamshid PiriDepartment of Water Engineering, Faculty of Water and Soil, University of Zabol, Zabol, Iran. j.piri@uoz.ac.ir.
Afsaneh BarkhordarDepartment of Chemistry, Faculty of Science, University of Zabol, Zabol, Iran.
Turan OzturkDepartment of Chemistry, Faculty of Science & Letters, Istanbul Technical University, Istanbul, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

White tea is valuable for having a high antioxidant content, which is considered to possess numerous beneficial effects on health. This study investigated the application of microwave-assisted extraction (MAE) for the extraction of total phenolic compounds from white tea. The experimental setup included four independent variables: microwave power (ranging from 100 to 300 W), extraction time (ranging from 10 to 40 min), temperature (ranging from 35 to 50 °C), and the ratio of food to solvent (ranging from 0.25 to 0.5 g/10 mL). The responses that were evaluated were IC

Indexed as

AlgorithmsMachine LearningTeaInhibitory Concentration 50PhenolsPhenolsTeaGenetic algoritmGMDHHarmony searchMicrowave assisted extractionWhite tea

Identifiers

PMID39468319
PMCPMC11519948

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.