MétaCan
Menu
Back to cohort
Record W1976317416 · doi:10.1007/s11746-013-2252-x

γ‐Oryzanols of North American Wild Rice (<i>Zizania palustris</i>)

2013· article· en· W1976317416 on OpenAlexafffund
Felix Aladedunye, Roman Przybylski, Magdalena Rudzińska, Dorota Klensporf‐Pawlik

Bibliographic record

VenueJournal of the American Oil Chemists Society · 2013
Typearticle
Languageen
FieldChemistry
TopicEdible Oils Quality and Analysis
Canadian institutionsUniversity of Lethbridge
FundersAgriculture Funding Consortium
KeywordsBrown riceOryza sativaFerulic acidBranOryzaComposition (language)Food scienceChemistryRice bran oilBotanyBiologyJaponicaWhite riceBiochemistryEcologyRaw material

Abstract

fetched live from OpenAlex

Abstract γ‐Oryzanol, a natural mixture of ferulic acid esters of triterpene alcohols and sterols, are an important bioactive components present in rice bran oil. In light of the recent increase in the popularity of wild rice among consumers, and the possibility of a direct relationship between γ‐oryzanol composition and its bioactivity, the oryzanol profile of major wild rice ( Zizania palustris ) grown in North America was studied and compared to regular brown rice ( Oryza sativa L.). A total of twenty‐three γ‐oryzanol components were separated, identified and quantified by HPLC coupled to an Orbitrap MS. The distribution of individual γ‐oryzanols was similar for all the wild rice but significantly different from those of the regular brown rice. Unlike in the regular brown rice, a significant amount of steryl caffeate and cinnamate were found in the wild rice samples. Generally, the amounts of γ‐oryzanol in the wild rice were higher compared to the regular brown rice, 1,352 vs. 688 μg/g. The results from this study showed that wild rice had a more diverse γ‐oryzanol composition and the higher amounts compared to the regular brown rice.

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)0.000
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 score0.179
Threshold uncertainty score0.849

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.235
Teacher spread0.226 · 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

Citations39
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the American Oil Chemists SocietySame topicEdible Oils Quality and AnalysisFrench-language works237,207