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Record W2384138054

Effects of Pine Nut Oil Extracted by Different Methods and Microwave Heating on Quality of Oil

2015· article· en· W2384138054 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

VenueFood and Nutrition in China · 2015
Typearticle
Languageen
FieldNursing
TopicNuts composition and effects
Canadian institutionsScience North
Fundersnot available
KeywordsNutPeroxide valueAcid valuePulp and paper industryChemistryExtraction (chemistry)Heat of combustionMicrowaveSolventFood scienceOil millMicrowave heatingBrazil nutChromatographyOrganic chemistryPalm oilBiochemistryCombustion
DOInot available

Abstract

fetched live from OpenAlex

Lipids oxidation is a major cause of quality deterioration in foods. To monitor the pine nuts oil extracted by different methods during microwave heating,physico-chemical properties and fatty acid composition of pine nut oil extracted by the aqueous enzymatic and the solvent methods were analyzed. Results showed that the two methods of extraction of pine nut oil quality were different. The aqueous enzymatic pine nuts acid value and phospholipid content were lower than those of solvent pine nut oil,while the peroxide value was higher than those of solvent pine nut oil. Extraction methods on the pine nut oil fatty acid composition was not significant,and effects of microwave heating on the quality of pine nut oil had not been reported. We also studied the effect of certain power( 700W),heating time( 1,3,5 and 7 min) on pine nut oil of the two methods quality to evaluate the security of the pine nut oil by microwave heating. Microwave heating induced severe quality and composition losses,mainly above 3 min of microwave heating,regardless the sample tested,so long time heating should be avoided in the microwave heating process of pine nut 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)0.000
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 score0.056
Threshold uncertainty score0.505

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 head0.024
GPT teacher head0.337
Teacher spread0.313 · 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