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Record W2742760304 · doi:10.30969/acsa.v11i2.614

Caracterização agroclimática e aptidão de culturas para diferentes municípios e regiões da Paraíba

2015· article· pt· W2742760304 on OpenAlexaff
Raimundo Mainar de Medeiros, Paulo Roberto Megna Francisco, Rigoberto Moreira de Matos, Djail Santos, Thiago Pereira de Sousa

Bibliographic record

VenueAGROPECUÁRIA CIENTÍFICA NO SEMIÁRIDO · 2015
Typearticle
Languagept
FieldAgricultural and Biological Sciences
TopicAgricultural and Food Sciences
Canadian institutionsCanadian Turfgrass Research Foundation
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

O zoneamento agroclimático é um extraordinário processo de informação do potencial agrícola de uma dada localidade e define a melhor época de plantio, as culturas adequadas ao cultivo na região e identifica áreas com maior potencial agrícola para sua produtividade. Objetivou-se caracterizar o clima e efetivar o zoneamento agroclimático para dez culturas apontando as suas possíveis aptidões de cultivo para os municípios de Alhandra, Araruna, Bananeiras, Santa Luzia, São João do Cariri e Teixeira. Utilizou-se uma série histórica de precipitação e temperatura do ar média para a realização do cálculo do balanço hídrico climatológico, classificação climática, construção do evapopluviograma e zoneamento agroclimático das culturas. Todas as culturas estudadas são aptas ao cultivo em todos os municípios, desde que seja adotado um sistema de irrigação. O uso da irrigação torna-se indispensável, principalmente nos meses que apresentam maior déficit hídrico, podendo adotar o manejo da irrigação com base nos dados históricos de evapotranspiração e desta forma garantir a produtividade máxima das culturas.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.601
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.004

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 head0.078
GPT teacher head0.265
Teacher spread0.188 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueAGROPECUÁRIA CIENTÍFICA NO SEMIÁRIDOSame topicAgricultural and Food SciencesFrench-language works237,207