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Development, Characterization, and Utilization of Food-Grade Polymer Oleogels

2016· review· en· W2228347103 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.

Bibliographic record

VenueAnnual Review of Food Science and Technology · 2016
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicFood Chemistry and Fat Analysis
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPolymerEthyl celluloseMaterials scienceRheologySolventPolymer scienceChemical engineeringFood productsStructuringCharacterization (materials science)Organic chemistryChemistryFood scienceNanotechnologyComposite materialBusiness

Abstract

fetched live from OpenAlex

The potential of organogels (oleogels) for oil structuring has been identified and investigated extensively using different gelator-oil systems in recent years. This review provides a comprehensive summary of all oil-structuring systems found in the literature, with an emphasis on ethyl-cellulose (EC), the only direct food-grade polymer oleogelator. EC is a semicrystalline material that undergoes a thermoreversible sol-gel transition in the presence of liquid oil. This unique behavior is based on the polymer's ability to associate through physical bonds. These interactions are strongly affected by external fields such as shear and temperature, as well as by solvent chemistry, which in turn strongly affect final gel properties. Recently, EC-based oleogels have been used as a replacement for fats in foods, as heat-resistance agents in chocolate, as oil-binding agents in bakery products, and as the basis for cosmetic pastes. Understanding the characteristics of the EC oleogel is essential for the development of new applications.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
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 head0.035
GPT teacher head0.287
Teacher spread0.252 · 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