MétaCan
Menu
Back to cohort
Record W1810628743 · doi:10.1002/ejlt.201300288

Micronutrient content of cold‐pressed, hot‐pressed, solvent extracted and RBD canola oil: Implications for nutrition and quality

2013· article· en· W1810628743 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

VenueEuropean Journal of Lipid Science and Technology · 2013
Typearticle
Languageen
FieldChemistry
TopicEdible Oils Quality and Analysis
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCanolaChemistryPhytosterolPolyphenolFood scienceExtraction (chemistry)TocopherolSolventChromatographyAntioxidantOrganic chemistryVitamin E

Abstract

fetched live from OpenAlex

In this study the quality characteristics and content of healthy minor components of four crude canola oils as an effect of different oil extraction method (solvent extraction, hot pressing, and cold pressing) were studied. Cold‐pressed canola oils had lower concentrations of FFA, PV, p ‐AV and chlorophylls than solvent‐extracted, and hot‐pressed canola oils. Oils obtained via the different extraction methods had different fatty acid profiles as well as dissimilar amounts of tocopherols, phytosterols, and polyphenols. The amount of total tocopherols in solvent‐extracted canola oil was 493 mg/kg compared to 388 mg/kg for hot‐pressed canola oil. The tocopherol content for two other cold‐pressed and one other RBD canola oil was 366, 354, and 327 mg/kg, respectively. Solvent‐extracted canola oil exhibited the highest free phytosterol content (178 mg/100 g), while RBD canola oil only had 129 mg/100 g of free phytosterols. While cold‐pressed canola oil had the lowest amount of polyphenols, traditional refining resulted in almost complete removal of polyphenols from canola oil.

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)0.001
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 score0.047
Threshold uncertainty score0.379

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.052
GPT teacher head0.286
Teacher spread0.235 · 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