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Record W2088978330 · doi:10.1021/jf4019239

Quality Assessment of Japanese Knotweed (Fallopia japonica) Grown on Prince Edward Island as a Source of Resveratrol

2013· article· en· W2088978330 on OpenAlexafffundabout
Huaguo Chen, Tina Tuck, Xiuhong Ji, Xin Zhou, Glen Kelly, Alain Cuerrier, Junzeng Zhang

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2013
Typearticle
Languageen
FieldMedicine
TopicSirtuins and Resveratrol in Medicine
Canadian institutionsUniversité de MontréalNational Research Council Canada
FundersNational Research Council Canada
KeywordsEmodinAnthraquinonesResveratrolBotanyPolygonaceaeBiologyTraditional medicineMedicine

Abstract

fetched live from OpenAlex

Japanese knotweed (Fallopia japonica , also known as Polygonum cuspidatum) is a common invasive plant species on Prince Edward Island (PEI), Canada, whereas it has been used in Chinese medicine and more recently as a raw material for extracting resveratrol. This paper reports on the quantification of resveratrol, polydatin, emodin, and physcion in roots, stems, and leaves of Japanese knotweed samples from PEI and British Columbia (BC), Canada, and nine provinces of China, by ultraperformance liquid chromatography (UPLC). The results showed that the root contains a much higher level of resveratrol than the stem and leaf, and it is accumulated in its highest level in October. PEI-grown knotweed contains similar levels of resveratrol and polydatin compared to Chinese samples collected in the month of October, but the contents of the other anthraquinones (emodin and physcion) are different. As such, Japanese knotweed grown in PEI could be a commercially viable source of raw material for resveratrol production; however, caution has to be taken in harvesting the right plant species.

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 score0.951
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.012
GPT teacher head0.273
Teacher spread0.261 · 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

Citations71
Published2013
Admission routes3
Has abstractyes

Explore more

Same venueJournal of Agricultural and Food ChemistrySame topicSirtuins and Resveratrol in MedicineFrench-language works237,207