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Record W2774697164 · doi:10.1002/lite.201700030

The effect of emulsifier type on the formation and stability of nanoemulsion gels

2017· article· en· W2774697164 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

VenueLipid Technology · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProteins in Food Systems
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsEmulsionVolume fractionChemical engineeringRheologyVolume (thermodynamics)Fraction (chemistry)ViscoelasticityMaterials scienceChromatographyOil dropletSurface-area-to-volume ratioChemistryComposite materialThermodynamics

Abstract

fetched live from OpenAlex

Summary Liquid nanoemulsions are shown to transform into viscoelastic gels by reducing droplet size, increasing interfacial repulsive barrier between the nanodroplets and therefore increasing the effective oil volume fraction. The repulsive gelation in nanoemulsions can be achieved at a significantly lower oil volume fraction compared to conventional emulsion gels, making the nanoemulsion gel an attractive material for various low‐fat food applications. Gelation in nanoemulsions stabilized by anionic small molecule emulsifier and polymeric protein are compared in terms of gel strength, average droplet size, effective oil volume fraction, and long‐term gel stability. It is expected that higher stability and large surface area of nanoscale droplet size can further extend the application of nanoemulsion gels in the field of functional foods, cosmetics and pharmaceuticals.

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)0.001
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 score0.232
Threshold uncertainty score0.262

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.022
GPT teacher head0.239
Teacher spread0.217 · 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