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Record W4411534834 · doi:10.1039/9781837676699-00128

Rheological Properties and Structures of Colloidal Oleogels and Hydrogels

2025· book-chapter· en· W4411534834 on OpenAlexaff
Kenneth Truong, Alejandro G. Marangoni

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicFood Chemistry and Fat Analysis
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsRheologySelf-healing hydrogelsColloidMaterials sciencePolymerColloidal particleChemical engineeringCaseinIonic strengthNanotechnologyChemistryPolymer chemistryComposite materialOrganic chemistryAqueous solution

Abstract

fetched live from OpenAlex

The macroscopic rheological properties of colloidal networks of proteins, polysaccharides, fat crystals and oleogelators are a function of the amount of network material present, the size and shape of the colloids and their aggregates and the strength of their inter-colloidal interactions. Here we will outline the development of quantitative models describing the relationships between the nano- and mesoscale structures of colloidal and polymer protein hydrogels and lipid oleogels and their macroscopic rheological and mechanical properties. These quantitative models will be used to showcase their usefulness in a variety of systems, from edible fats and oleogels to whey protein isolates and casein gels. The successful development of new food products requires a fundamental knowledge of the relationship between structures at different length scales and their physical properties.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.184
Teacher spread0.162 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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