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Características e atributos de Latossolos sob diferentes usos na região Oeste do Estado da Bahia

2016· article· pt· W2536730811 on OpenAlexaboutno aff
Ademir Fontana, Wenceslau Geraldes Teixeira, Fabiano de Carvalho Balieiro, Thayane Pires Alves de Moura, Andressa Rosas de Menezes, Camila Santana

Bibliographic record

VenuePesquisa Agropecuária Brasileira · 2016
Typearticle
Languagept
FieldAgricultural and Biological Sciences
TopicSoil Management and Crop Yield
Canadian institutionsnot available
Fundersnot available
KeywordsPhysics

Abstract

fetched live from OpenAlex

Resumo O objetivo deste trabalho foi avaliar os efeitos de diferentes usos da terra nas características e nos atributos de Latossolos da região Oeste do Estado da Bahia. Os Latossolos apresentavam texturas com fração areia amplamente predominante, e foram avaliados em áreas de cerrado, algodão, soja e feijão, no Município de Luís Eduardo Magalhães. A caracterização morfológica e a coleta de amostras de solos para avaliação dos atributos físicos e químicos por horizontes foram feitas em minitrincheiras, enquanto a avaliação da condutividade hidráulica saturada foi feita com permeâmetro de Guelph em duas profundidades: 0,0-0,20 e 0,20-0,40 m. Os Latossolos avaliados, além de uma estrutura maciça, apresentaram horizonte genético adensado, que, sob uso agrícola, torna-se mais compactado, espesso e superficial, e forma torrões quando revolvido. O uso agrícola reduz a condutividade hidráulica saturada dos Latossolos avaliados nas duas camadas, com exceção do cultivo de feijão.

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)0.000
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 score0.076
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.032
GPT teacher head0.252
Teacher spread0.221 · 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

Citations34
Published2016
Admission routes1
Has abstractyes

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