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Antioxidant and Anticancer Activities of Raspberry Extracts

2015· article· en· W359122237 on OpenAlexvenueno aff
Youqiu Xue, Kejun Cheng, Jian-Ge Qiu, Xiao-Long Mei, Wenji Zhang, Qiwei Jiang, Wu-Ming Qin, Yang Yang, Di-Wei Zheng, Yao Chen, Meng-Ning Wei, Dongmei Huo, Xing Wei, Zhi Shi

Bibliographic record

VenueJournal of cancer research updates · 2015
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsnot available
Fundersnot available
KeywordsBlowing a raspberryRubusAntioxidantEthyl acetateChemistryPolyphenolPetroleum etherDPPHBerryEthanolTraditional medicineAlcoholChloroformFood scienceBiochemistryBotanyOrganic chemistryBiologyExtraction (chemistry)Medicine

Abstract

fetched live from OpenAlex

The raspberry (Rubus idaeus) is an economical important berry crop that contains phytochemicals such as polyphenols and flavonoids with potential health benefits. This study addresses the antioxidant and anticancer effects of raspberry and its root extracts. Raspberry and raspberry root were extracted with ethanol, and separated into petroleum ether, chloroform, ethyl acetate, n-butyl alcohol and water fraction. Most extracts showed the powerful activities to scavenge DPPH radical, eliminate hydroxyl free radical ion, and inhibit the growth of human cancer cells, suggesting their promising application on health care.

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)0.001
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.308

Codex and Gemma teacher scores by category

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

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 head0.106
GPT teacher head0.438
Teacher spread0.332 · 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 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

Citations1
Published2015
Admission routes1
Has abstractyes

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