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Record W4402705460 · doi:10.1016/j.jobab.2024.09.002

Cavitation as a zero-waste circular economy process to convert citrus processing waste into biopolymers in high demand

2024· article· en· W4402705460 on OpenAlexvenueno aff
Rosaria Ciriminna, Giuseppe Angellotti, Giovanna Li Petri, Francesco Meneguzzo, Cristina Riccucci, Gabriella Di Carlo, Mario Pagliaro

Bibliographic record

VenueJournal of Bioresources and Bioproducts · 2024
Typearticle
Languageen
FieldMaterials Science
TopicNanocomposite Films for Food Packaging
Canadian institutionsnot available
Fundersnot available
KeywordsZero wasteCircular economyWaste managementProcess (computing)Food wasteCavitationZero emissionEnvironmental scienceZero (linguistics)EngineeringEcologyComputer scienceMechanicsBiology

Abstract

fetched live from OpenAlex

Cavitation in water only, no matter whether hydrodynamic or acoustic, is a zero-waste circular economy process to convert industrial citrus processing waste into high-performance polysaccharides in high demand in a single-step at room temperature and ambient pressure using a modest amount of electricity as the only energy input. Following previous reports in which we used hydrodynamic cavitation, we now use an industrial acoustic sonicator to demonstrate the general viability of cavitation to convert biowaste residue of the industrial squeezing of pigmented sweet orange ( Citrus sinensis ) into highly bioactive “IntegroPectin” pectin and micronized cellulose “CytroCell”. From biomedicine through advanced composite membranes, said biomaterials hold great applicative potential. We conclude discussing the economic and technical feasibility of industrial implementation of the “CytroCav” process.

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)0.001
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 score0.009
Threshold uncertainty score0.719

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.006
GPT teacher head0.243
Teacher spread0.237 · 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

Citations15
Published2024
Admission routes1
Has abstractyes

Explore more

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