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Record W3204207265 · doi:10.1016/j.lwt.2021.112508

Strategies for controlling over-puffing of 3D-printed potato gel during microwave processing

2021· article· en· W3204207265 on OpenAlexaff
Xiuxiu Teng, Min Zhang, Arun S. Mujumdar

Bibliographic record

VenueLWT · 2021
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsMcGill University
Fundersnot available
KeywordsMaterials scienceParticle sizeMicrowavePorosityComposite materialStarchResidue (chemistry)Hardening (computing)MoistureChemistryFood scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Starch-based printed foods are very sensitive to rapid heating using microwaves because microwave energy accelerates gelatinization of starch and formation of the gel network, which enhances the ability of foods to hold water vapor, resulting in the over-puffing problem of printed samples. Insoluble dietary fiber extracted from soybean residue (SIDF, soybean insoluble dietary fiber) and modification of the internal structure provided a solution to the over-puffing problem. Experimental results showed that incorrect addition and particle size of SIDF caused excess puffing or hardening. SIDF addition of 10% (w/w) and particle size of 150–180 μm provided better crispness while maintaining the product shape. The effect of SIDF on expansion rate was attributed to reduced mobility of moisture, enhanced mechanical strength, and declined deformation ability of potato gel. Internal structures with parallel lines and high porosity should be selected and the maximum internal filling density was generally less than 70%. Besides controlling deformation, it added value of soybean residue by incorporating into 3D-printed puffed potato chips.

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 score0.068
Threshold uncertainty score0.687

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 head0.012
GPT teacher head0.229
Teacher spread0.217 · 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

Citations19
Published2021
Admission routes1
Has abstractyes

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