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Record W2774824221 · doi:10.1093/fqsafe/fyx028

Co-encapsulation of bioactives for food applications

2017· article· en· W2774824221 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

VenueFood Quality and Safety · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMicroencapsulation and Drying Processes
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsEncapsulation (networking)ChemistryNanotechnologyEmulsionControlled releaseBiochemical engineeringComputer scienceMaterials scienceBiochemistryEngineering

Abstract

fetched live from OpenAlex

Co-encapsulation of bioactive is an emerging field which shows promising approach to develop functionally active food products. Health-promoting components including antioxidants, vitamins, essential oils or flavors, and antimicrobials could be successfully delivered in functional foods by co-encapsulating in suitable wall matrix. Co-encapsulation is especially useful as this concept takes into account the synergistic effect of multiple bioactives in enhancing bioactivity to target specific health benefits. The review focusses on various factors governing the stability of the microencapsulated system such as drying methods and temperature, selection of wall material, surfactant, co-excipient, emulsion homogenizing speed, and appropriate combination of the bioactive for co-encapsulation to get synergistic effects. Effective results have been demonstrated by several researchers, but further studies would help in unravelling the full potential of this technique in food system.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.864
Threshold uncertainty score0.461

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 studies0.0010.000
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 head0.119
GPT teacher head0.350
Teacher spread0.231 · 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