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Canola Proteins at the Air–Water Interface

2025· article· en· W4412956389 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

VenueACS Food Science & Technology · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProteins in Food Systems
Canadian institutionsUniversity of British Columbia
FundersCanada Foundation for Innovation
KeywordsCanolaInterface (matter)Air waterEnvironmental scienceBiologyEngineeringAgronomyChemical engineeringMechanicsPhysicsPulmonary surfactant

Abstract

fetched live from OpenAlex

This study investigated the interfacial behavior and viscoelastic properties of canola proteins at air–water interfaces in the presence or absence of salt. Pendant drop tensiometry, kinetic modeling, compression isotherms, Brewster angle microscopy (BAM), and dilatational rheology have been employed. Salt accelerates protein adsorption at the air–water interface, but it does not affect diffusion or rearrangement kinetics. The construction of compression isotherms revealed the formation of irreversible 2D networks, and BAM imaging showed microstructural faults. The elasticity and irreversibility of these films were confirmed using dilatational rheology, where the elastic modulus remained frequency-independent throughout the experimental window. Protein films were largely unaltered by salt in the linear viscoelastic range of the interface. However, notable effects were observed outside the linear viscoelastic range, where salt influenced mechanical responses, leading to strain-hardened interfaces. This study links the structural characteristics of canola protein to its functionalities, suggesting improvements in interfacial properties for sustainable foods.

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 score0.106
Threshold uncertainty score0.874

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0020.002
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 head0.015
GPT teacher head0.240
Teacher spread0.225 · 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