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Record W3106922727 · doi:10.3390/molecules25235563

Carrageenan-Based Films Incorporated with Jaboticaba Peel Extract: An Innovative Material for Active Food Packaging

2020· article· en· W3106922727 on OpenAlexafffund
Luisa Bataglin Avila, Elis Regina Correa Barreto, Paloma Krolow de Souza, Bárbara De Zorzi Silva, Thamiris Renata Martiny, Caroline Costa Moraes, Marcílio Machado Morais, Vijaya Raghavan, Gabriela Silveira da Rosa

Bibliographic record

VenueMolecules · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeaweed-derived Bioactive Compounds
Canadian institutionsMcGill University
FundersUniversidade Federal do PampaFundação de Amparo à Pesquisa do Estado do Rio Grande do SulNatural Sciences and Engineering Research Council of CanadaCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsCarrageenanActive packagingExtraction (chemistry)Food packagingAntioxidantMaterials scienceFood scienceSolubilityHomogeneousChemistryChemical engineeringChromatographyMathematicsOrganic chemistry

Abstract

fetched live from OpenAlex

This research investigated the bioactive potential of jaboticaba peel extract (JPE) and proposed an innovative material for food packaging based on carrageenan films incorporated with JPE. The extract was obtained through microwave assisted extraction (MAE) according to central composite rotational design and the optimized conditions showed a combined antimicrobial and antioxidant actions when the extraction process is accomplished at 80 °C and 1 min. The carrageenan film incorporated with JPE was manageable, homogeneous and the presence of JPE into film increased the thickness and improved the light barrier of the film. The results of solubility and mechanical properties did not show significant differences. The benefit of using MAE to improve the recovery of bioactive compounds was demonstrated and the carrageenan film with JPE showed a great strategy to add additives into food packaging.

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 score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.039
GPT teacher head0.229
Teacher spread0.190 · 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

Citations40
Published2020
Admission routes2
Has abstractyes

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