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Record W3097851763 · doi:10.1016/j.heliyon.2020.e05294

Characterizing internal cavity modulation of corn starch microcapsules

2020· article· en· W3097851763 on OpenAlexafffund
David Wulff, A.Y.F. Chan, Qiang Liu, Frank Gu, Marc G. Aucoin

Bibliographic record

VenueHeliyon · 2020
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of TorontoNational Institute for NanotechnologyUniversity of Waterloo
FundersAgriculture and Agri-Food CanadaNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsSwellingScanning electron microscopeMaterials scienceStarchConfocal laser scanning microscopyMicroscopyParticle sizeComposite materialChemical engineeringBiomedical engineeringChemistryOpticsFood science

Abstract

fetched live from OpenAlex

Swelling of normal corn starch granules through heating in water leads to enlargement of the starch particles and a corresponding increase in internal cavity size. Through control of the swelling extent, it is possible to tune the size of the internal cavity for the starch microcapsules (SMCs). The swelling extent can be controlled through regulation of the swelling time and the swelling temperature. Since the swelling extent is correlated with particle size and solubility, these aspects may also be controlled. Imaging the SMCs at increasing levels of swelling extent using scanning electron microscopy (SEM) allowed for the internal cavity swelling process to be clearly observed. Brightfield and polarizing light microscopy validated the SEM observations. Confocal laser scanning microscopy provided further validation and indicated that it is possible to load the SMCs with large molecules through diffusion. The highly tunable SMCs are novel microparticles which could have applications in various industries.

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 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 score0.048
Threshold uncertainty score0.250

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 head0.039
GPT teacher head0.262
Teacher spread0.223 · 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 teacher head, 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

Citations12
Published2020
Admission routes2
Has abstractyes

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