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Faixa de suficiência para a cultura do algodão no centro-oeste do Brasil: II. micronutrientes

2012· article· pt· W4235270146 on OpenAlexaff
Marcos Antônio Camacho, William Natale, José Carlos Barbosa

Bibliographic record

VenueCiência Rural · 2012
Typearticle
Languagept
FieldAgricultural and Biological Sciences
TopicSoil Management and Crop Yield
Canadian institutionsNutrition International
Fundersnot available
KeywordsGossypium hirsutumHorticultureBiologyPhysics

Abstract

fetched live from OpenAlex

Com o objetivo de estabelecer a faixa de suficiência dos micronutrientes para o algodoeiro, foi utilizado o método da chance matemática para dados de monitoramento nutricional de três localidades produtoras de algodão no cerrado brasileiro, avaliando 152 áreas. O método da chance matemática foi adequado para estabelecer padrões de referência nutricional no algodoeiro, podendo subsidiar parâmetros que a pesquisa convencional não alcançaria em curto espaço de tempo. As faixas encontradas para os micronutrientes com o método da chance matemática tendo como referência a produtividade de 4000kg ha-1 foram, em mg kg-1, de 41-89; 4-14; 90-230; 23-110 e 25-50 para B, Cu, Fe, Mn e Zn, respectivamente, enquanto para a produtividade de 4500kg ha-1 foram, em mg kg-1, de 53-83; 4-12; 110-440; 40-60 e 25-50 para B, Cu, Fe, Mn e Zn, respectivamente. As faixas indicadas, embora semelhantes às recomendações existentes, demonstram aperfeiçoamento para obtenção de altas produtividades. As limitações do método poderão ser atenuadas com a ampliação do sistema de monitoramento nutricional nas lavouras de algodoeiro.

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)0.001
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 score0.080
Threshold uncertainty score0.159

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.018
GPT teacher head0.238
Teacher spread0.220 · 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

Citations2
Published2012
Admission routes1
Has abstractyes

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