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Record W4213268541 · doi:10.1080/10408398.2022.2039896

Application of carbon dots in food preservation: a critical review for packaging enhancers and food preservatives

2022· review· en· W4213268541 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

VenueCritical Reviews in Food Science and Nutrition · 2022
Typereview
Languageen
FieldMaterials Science
TopicCarbon and Quantum Dots Applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsFood packagingPreservativeActive packagingFood PreservativesShelf lifeBiocompatibilityNanotechnologyFood preservationFood scienceCoatingMaterials scienceChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Carbon dots (CDs) have two unique advantages: one is ease of synthesis at low price, the other is desirable physical and chemical properties, such as ultra-small size, abundant surface functional groups, nontoxic/low-toxicity, good biocompatibility, excellent antibacterial and antioxidant activities etc. These advantages provide opportunities for the development of new food packaging enhancers and food preservatives. This paper systematically reviews the studies of CDs used to strengthen the physical properties of food packaging, including strengthen mechanical strength, ultraviolet (UV) barrier properties and water barrier properties. It also reviews the researches of CDs used to fabricate active packaging with antioxidant and/or antibacterial properties and intelligent packaging with the capacity of sensing the freshness of food. In addition, it analyzes the antioxidant and antibacterial properties of CDs as preservatives, and discusses the effect of CDs applied as coating agents and nano-level food additives for extension the shelf life of food samples. It also provides a brief review on the security and the release behavior of CDs.

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)0.005
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.925
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.155
GPT teacher head0.418
Teacher spread0.263 · 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