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Record W2055234320

CONFIRMING THE CHEMICAL STRUCTURE OF ANTIOXIDATIVE TRIHYDROXYFLAVONES FROM SCUTELLARIA BAICALENSIS USING MODERN SPECTROSCOPIC METHODS

2005· article· en· W2055234320 on OpenAlexaff
Ronald B. Pegg, Ryszard Amarowicz, Jan Oszmiański

Bibliographic record

VenuePolish Journal of Food and Nutrition Sciences · 2005
Typearticle
Languageen
FieldMedicine
TopicFlavonoids in Medical Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsBaicaleinBaicalinScutellaria baicalensisChemistryMass spectrometryChromatographyWogoninHigh-performance liquid chromatographyBiologyTraditional Chinese medicine
DOInot available

Abstract

fetched live from OpenAlex

Phenolics were extracted from the roots of Scutellaria baicalensis using methanol. The compounds 5,6,7-trihydroxyflavone and 5,6,7-trihydroxyflavone-7-O-β-D-glucopyrano-siduronate, which are commonly referred to as baicalein and baicalin, respectively, were isolated from the crude extract using a semi-preparative HPLC method on a RP-18 column. The identities of the separated trihydroxyflavones were determined by electron impact (El), chemical ionisation (CI) and/or fast atom bombardment (FAB) mass spectrometry and confirmed by 1 H, 13 C( 1 H), HMQC and HMBC-NMR spectral evidence to be baicalein and baicalin.

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 score0.002
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 head0.071
GPT teacher head0.426
Teacher spread0.355 · 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

Citations10
Published2005
Admission routes1
Has abstractyes

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Same venuePolish Journal of Food and Nutrition SciencesSame topicFlavonoids in Medical ResearchFrench-language works237,207