MétaCan
Menu
Back to cohort
Record W3097268665 · doi:10.3390/foods9111559

Aroma, Quality, and Consumer Mindsets for Shelf-Stable Rice Thermally Processed by Reciprocal Agitation

2020· article· en· W3097268665 on OpenAlexfundno aff
William R. Dixon, Blanca E. Morales‐Contreras, Manoch Kongchum, Zhimin Xu, Dustin L. Harrell, Howard Moskowitz, Louise Wicker

Bibliographic record

VenueFoods · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGABA and Rice Research
Canadian institutionsnot available
FundersAgricultural Center, Louisiana State UniversityHatchLouisiana Board of Regents
KeywordsCookerAromaFood scienceAmyloseStarchChemistryMathematicsBiology

Abstract

fetched live from OpenAlex

Food engineering, food chemistry, and consumer segmentation were used to evaluate ready-to-eat rice. The aromatic Louisiana Clearfield Jazzman (CJ) and Thai Jasmine (TJ), and a non-aromatic parboiled (PB) rice were hydrated during the first 10 min of processing with reciprocal agitation followed by static retort processing. The aroma compound, 2-Acetyl-1-pyrroline (2-AP) was more heat-stable in CJ than TJ rice but decreased 15-fold compared to the rice cooker method. Pareto analysis indicated that rice type and agitation had the main effect on amylose and total starch and chroma and hue. Color differences of rice agitated during hydration and between rice cooker or static retort processed rice, indicated only slight differences for each rice variety. Hydration of dry rice during retort cooking and similar starch, color, and aroma quality were achieved with reciprocal compared to static or rice cooker methods. Survey responses categorized consumers into three, mindsets driven by rice consumption, convenience, or 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 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.894
Threshold uncertainty score0.119

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 head0.090
GPT teacher head0.321
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

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

Citations7
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueFoodsSame topicGABA and Rice ResearchFrench-language works237,207