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Record W2008059537 · doi:10.1007/s11746-009-1486-0

Determination of Sinapic Acid Derivatives in Canola Extracts Using High‐Performance Liquid Chromatography

2009· article· en· W2008059537 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of the American Oil Chemists Society · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNitrogen and Sulfur Effects on Brassica
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaCanola Council of Canada
KeywordsCanolaHigh-performance liquid chromatographyChemistryChromatographyFood science

Abstract

fetched live from OpenAlex

A high-performance liquid chromatographic (HPLC) method with diode array detection (DAD) was used to determine the total phenolics, including sinapic acid derivatives in canola. Ten Western Canadian canola seeds, six other commodity canola seeds, their corresponding press cakes and meals were analyzed. Seeds of European 00 rapeseed and Brassica Juncea (Indian mustard) were included for comparison. Phenolic compounds were separated using a gradient elution system of water-methanol-omicron-phosphoric acid solution with a flow rate of 0.8 ml/min. In addition to sinapine (SP) and sinapic acid (SA), sinapoyl glucose (SG) is reported in the methanolic extracts. The detection and quantification limits of these compounds were 0.20-0.40 and 0.50-0.80 mug/ml, respectively with recovery values over 98.0%. The content of total phenolics, SP, SA and SG in canola extracts ranged from 9.16 to 16.13, 6.39 to 12.28, 0.11 to 0.59 and 1.36 to 7.50 mg/g, respectively with significant differences among varieties.

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.

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 score0.019
Threshold uncertainty score0.397

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.006
GPT teacher head0.247
Teacher spread0.241 · 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