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Record W3089543492 · doi:10.1002/fsn3.1841

A comparative UPLC‐Q‐Orbitrap‐MS untargeted metabolomics investigation of different parts of <i>Clausena lansium</i> (Lour.) Skeels

2020· article· en· W3089543492 on OpenAlexaff
Ruiyi Fan, Cheng Peng, Xinxin Zhang, Diyang Qiu, Genlin Mao, Yusheng Lu, Jiwu Zeng

Bibliographic record

VenueFood Science & Nutrition · 2020
Typearticle
Languageen
FieldChemistry
TopicChromatography in Natural Products
Canadian institutionsMinistry of Agriculture
Fundersnot available
KeywordsMetabolomicsMetabolic pathwayOrbitrapChemistryBiologyChromatographyBiochemistryEnzymeMass spectrometry

Abstract

fetched live from OpenAlex

Abstract In this study, the non‐targeted large‐scale plant metabolomics (UPLC‐Q‐Orbitrap‐MS) was performed for the comparison of chemical profiling of the leaves, barks, flowers, peels, pulps, and seeds of Clausena lansium (Lour.) Skeels (called “wampee”). A total of 364 metabolites were identified, and 62 potential biomarkers were selected by the multivariate statistical analysis. Hierarchical cluster analysis suggested that the selected biomarkers were significant differential metabolites among various parts of wampee. Metabolic pathway analysis showed a significant enrichment of the “Flavone and flavonol synthesis” and “Isoquinoline alkaloid biosynthesis” pathway. This study provides important information for the isolation and identification of functional components from different tissues of wampee and the metabolic biosynthesis pathway elucidation in detail.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.036
GPT teacher head0.252
Teacher spread0.217 · 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 designObservational
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

Citations35
Published2020
Admission routes1
Has abstractyes

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