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Record W3113811497 · doi:10.33837/msj.v3i3.1260

AVALIAÇÃO PARTICIPATIVA E CONDIÇÕES AGROCLIMÁTICAS NO CULTIVO DO FEIJOEIRO EM SISTEMA ORGÂNICO

2020· article· pt· W3113811497 on OpenAlexfundno aff
Marciel Lelis Duarte, José Arcanjo Nunes, Sebastião Martins Filho

Bibliographic record

VenueMulti-Science Journal · 2020
Typearticle
Languagept
FieldAgricultural and Biological Sciences
TopicAgronomic Practices and Intercropping Systems
Canadian institutionsnot available
FundersDanish International Development AgencyInternational Fund for Agricultural DevelopmentConsortium of International Agricultural Research CentersInternational Development Research CentreCrop TrustOPEC Fund for International Development
KeywordsPhysicsHorticultureHumanitiesBiologyArt

Abstract

fetched live from OpenAlex

O presente estudo teve como objetivo a avaliação participativa de genótipos locais e melhorados de feijoeiro associados às condições agroclimáticas em sistema de cultivo orgânico. O trabalho conjunto entre o setor formal e o setor informal, geralmente representado pelas comunidades rurais, pode contribuir no uso e conservação de germoplasma adaptado aos agroecossistemas das comunidades agrícolas e, além disso, o melhoramento participativo é sem dúvida uma excelente estratégia para o desenvolvimento sustentável de comunidades de agricultores familiares, pois o agricultor passa a ser corresponsável pela pesquisa deixando de ser um elemento passivo dentro do processo. Os experimentos foram conduzidos em condições de campo, sob cultivo orgânico, na comunidade agrícola de Fortaleza, situada no município de Muqui-ES. Foram utilizados 39 genótipos entre cultivares melhorados que são cultivados na região e genótipos locais, nos anos de 2006, 2007 e 2008. O delineamento experimental utilizado foi o de blocos ao acaso, com quatro repetições. Foi verificado que nos anos de 2006, 2007 e 2008 houve poucas diferenças entre os genótipos nas características avaliadas, exceto para a produção de grãos. A baixa precipitação no ano de 2006 e as altas temperaturas no ano de 2008 influenciaram a baixa produção de grãos dos genótipos.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.134
GPT teacher head0.331
Teacher spread0.197 · 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 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

Citations1
Published2020
Admission routes1
Has abstractyes

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