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Record W2982622833 · doi:10.3390/foods8110533

Consumer Preferences and Sensory Profile Related to the Physico-Chemical Properties and Texture of Different Maize Tortillas Types

2019· article· en· W2982622833 on OpenAlexfundno aff
Mădălina Ungureanu‐Iuga, Víctor Ávila-Akerberg, Tanya M. González Martínez, Silvia Mironeasa

Bibliographic record

VenueFoods · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsnot available
FundersOntario Ministry of Research and Innovation
KeywordsTexture (cosmology)Sensory systemFood scienceSensory analysisChemistryPsychologyComputer scienceCognitive psychologyArtificial intelligence

Abstract

fetched live from OpenAlex

Maize tortilla is a basic food in Mexico, and, lately, the food industry has tried to make the manufacturing process easier by using instant flours and specialized machines. The purpose of this study was to investigate consumers' behaviors related to tortillas and to evaluate the sensory, textural, and physico-chemical parameters of tortillas from the Tlazala region, Mexico. The sensory profile revealed that the artisanal ones had better parameters in terms of smell, taste, and appearance compared to the others. These results are consistent with consumers' preferences for tortillas made of maize grain instead of industrial corn flour. The sensory parameters and the physico-chemical and texture profile parameters varied with the maize type and manufacturing process. Our findings showed that the artisanal hand-made ones were more nutritious, followed by those mechanically made using maize grain, and finally by those mechanically made from industrialized corn flour. The results of this study may help processors to better understand the parameters of their products and people's preferences.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.414
Threshold uncertainty score0.504

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 head0.009
GPT teacher head0.198
Teacher spread0.189 · 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 designObservational
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

Citations33
Published2019
Admission routes1
Has abstractyes

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