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Record W3213812206 · doi:10.15586/ijfs.v33i4.2025

Factors affecting the cooking quality of stored carioca beans (Phaseolus vulgaris)

2021· article· en· W3213812206 on OpenAlexaff
Juliana Aparecida Correia Bento, Karen Carvalho Ferreira, P. Z. Bassinello, B. Dave Oomah

Bibliographic record

VenueItalian Journal of Food Science · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant pathogens and resistance mechanisms
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBrowningPhaseolusCultivarFood scienceQuality (philosophy)LegumeBiologyHorticultureAgronomyPhysics

Abstract

fetched live from OpenAlex

The culinary quality of carioca beans is related to their market value and consumer acceptability. The depreciation of the cooking/technological quality of the product occurs mainly because of the integument browning and the longer cooking time of the grains, which are influenced by the storage time and conditions. The loss of culinary quality reduces the market value of carioca beans because consumers reject darkened grains that are attributed to a longer cooking time. As a result, cooking time (resistance to cooking), the color of the integument, and the texture of the cooked beans are determinant factors in the acceptance of carioca bean cultivars. The browning of the grain integument and the cooking time mainly depends on the environmental conditions, storage time, the tegument of each genotype, and the chemical and physical properties of the cotyledons. Therefore, this review aims to survey the scientific literature on the extrinsic and intrinsic factors that affect the culinary quality of carioca beans.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.064
GPT teacher head0.269
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2021
Admission routes1
Has abstractyes

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Same venueItalian Journal of Food ScienceSame topicPlant pathogens and resistance mechanismsFrench-language works237,207