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Record W2943074061 · doi:10.5539/jas.v11n7p256

Analysis of the Production Chain of Bean Culture in Brazil

2019· article· en· W2943074061 on OpenAlex
Diandra Ganascini, Jéssica Cristina Urbanski Laureth, Isaque de Souza Mendes, Luciene Kazue Tokura, Eduardo Lange Sutil, Bruna de Villa, Alessandra Mayumi Tokura Alovisi, Ivã Luis Caon, Erivelto Mercante, Sílvia Renata Machado Coelho

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".

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural and Food Sciences
Canadian institutionsnot available
FundersFundação AraucáriaConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsBusinessProduction (economics)Supply chainCropProduct (mathematics)Work (physics)Quality (philosophy)Agricultural economicsAgricultural scienceValue chainYield (engineering)BeneficiationBiotechnologyMarketingEconomicsEngineeringBiologyAgronomyMathematics

Abstract

fetched live from OpenAlex

This bibliographical review brings information about the productive chain of beans, an essential product in the Brazilian diet, but present in several countries of the world. Beans are a source of protein, fiber, minerals and vitamins, allowing for healthy eating for easy access. Being, Brazil is the third largest producer of beans in the world, losing only to Myanmar and India, also the main consumer of beans in the world, having to import part of the beans consumed in Argentina. Due to iss, the bean culture is a promising crop, since the supply does not meet the domestic demand, being necessary the application of technologies that improve the yield and facilitate the cultivation. One of the obstacles of the crop is the susceptibility of the deterioration of the grains to store them, because, these grains stored, the commercial value tends to fall due to loss of quality. The objective of the work was to raise information on the productive chain of the beans. Periodicals, books, and information literatures were explored. Therefore, in view of the above, it was observed that in Brazil, the crop still needs to stimulate cultivation to supply domestic demand, improve storage conditions, invest in genetic improvement to maintain grain quality, and the study is necessary of new alternatives of destination for the residues generated by the processing and beneficiation of grains.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.805
Threshold uncertainty score0.406

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.008
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.010
GPT teacher head0.218
Teacher spread0.208 · 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