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Record W2740891446 · doi:10.13083/reveng.v23i5.601

PRODUÇÃO DE DIFERENTES CULTIVARES DE BATATA SOB DISTINTAS LÂMINAS DE IRRIGAÇÃO - DOI: 10.13083/1414-3984/reveng.v23n5p466-476

2015· article· pt· W2740891446 on OpenAlexaff
Sofia Michele Muchalak, Fernando França da Cunha, Renato Anastácio Guazina, Sebastião Ferreira de Lima, Amanda Regina Godoy

Bibliographic record

VenueRevista Engenharia na Agricultura - REVENG · 2015
Typearticle
Languagept
FieldAgricultural and Biological Sciences
TopicPotato Plant Research
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsHorticultureCultivarSowingBiology

Abstract

fetched live from OpenAlex

O máximo potencial produtivo das cultivares de batata e a qualidade dos tubérculos estão diretamente relacionados à disponibilidade hídrica no solo. Dessa forma, o objetivo do presente trabalho foi avaliar o efeito de distintas lâminas de irrigação nas características agronômicas de diferentes cultivares de batata na região nordeste de Mato Grosso do Sul. O experimento foi conduzido na Universidade Federal de Mato Grosso do Sul, campus de Chapadão do Sul, MS, utilizando-se o delineamento experimental de blocos ao acaso em parcelas subdivididas, com quatro repetições, tendo nas parcelas quatro lâminas de irrigação (50, 75, 100 e 125% da quantidade de água para suprir a perda de água por evapotranspiração da cultura) e nas subparcelas três cultivares de batata (Asterix, Atlantic e CLL). Avaliaram-se os resultados do número de tubérculos por planta, massa média do tubérculo, produtividade comercial e eficiência do uso da água (EUA). O aumento da lâmina de irrigação proporcionou redução na eficiência do uso da água pela batata; e não afetou as demais características avaliadas. A cultivar Asterix deve ser preferida pelos agricultores de batata do nordeste Sul Mato-Grossense.

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)0.005
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.310
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.079
GPT teacher head0.301
Teacher spread0.223 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueRevista Engenharia na Agricultura - REVENGSame topicPotato Plant ResearchFrench-language works237,207