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Record W2001414940 · doi:10.1007/s11746-013-2345-6

Production of Canolol from Canola Meal Phenolics via Hydrolysis and Microwave‐Induced Decarboxylation

2013· article· en· W2001414940 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.

Bibliographic record

VenueJournal of the American Oil Chemists Society · 2013
Typearticle
Languageen
FieldEngineering
TopicCatalysis for Biomass Conversion
Canadian institutionsCargill (Canada)University of Manitoba
Fundersnot available
KeywordsCanolaHydrolysisChemistryDecarboxylationEnzymatic hydrolysisEsteraseMealFood scienceOrganic chemistryNuclear chemistryEnzymeCatalysis

Abstract

fetched live from OpenAlex

Abstract A potent antioxidant, anti‐inflammatory and anti‐mutagenic agent; 4‐vinyl‐2,6‐dimethoxyphenol (canolol) was obtained from canola meal in a significant yield via alkaline (NaOH)/enzymatic (ferulic acid esterase) hydrolysis followed by microwave‐assisted decarboxylation. The hydrolysis was carried out either through using canola meal directly as a substrate or by using the 70 % aqueous methanolic extract filtrates. The hydrolyzed extracts underwent RP‐HPLC analysis which showed that 81.0 and 94.8 % of the total phenolics were hydrolyzed to sinapic acid after the alkaline hydrolysis of the meal and the methanolic extracts, respectively. The enzymatic hydrolysis showed lower conversion rates (49.5 and 58.3 %). The hydrolyzed extracts were consequently decarboxylated using 8‐diazabicyclo[5.4.0]undec‐7‐ene under microwave irradiation at different conditions. The HPLC profiling of decarboxylated extracts showed that using microwave at 300 W of microwave power for 12 min brought the highest sinapic acid conversion to canolol (58.3 %) yielding 4.2 mg canolol from each gram of canola meal suggesting that the process could be commercially economical.

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 score0.021
Threshold uncertainty score0.423

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 head0.004
GPT teacher head0.181
Teacher spread0.176 · 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