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Macrominerais para bovinos de corte nas pastagens nativas dos Campos de Cima da Serra - RS

2006· article· pt· W2075524418 on OpenAlexaff
Carolina Wunsch, Júlio Otávio Jardim Barcellos, Ênio Rosa Prates, Eduardo Castro da Costa, Y.R. Montanholi

Bibliographic record

VenueCiência Rural · 2006
Typearticle
Languagept
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPhysicsAnimal scienceHorticultureBiology

Abstract

fetched live from OpenAlex

Em face das poucas informações disponíveis sobre a composição mineral das pastagens nativas da região dos Campos de Cima da Serra (RS), o presente trabalho de pesquisa objetivou avaliar os teores dos principais macrominerais, em diferentes épocas do ano, e relacionar o perfil mineral destas pastagens com as necessidades nutricionais recomendadas pelo NRC (1996) para bovinos de corte. O projeto foi conduzido em vinte propriedades particulares, em Cambará do Sul, utilizando áreas de campo nativo que estavam sendo normalmente utilizadas em pastoreio por bovinos de corte e/ou ovinos e que não tinham sofrido nenhum tipo de melhoria, reforma ou recuperação (exceto queimada), no mínimo nos últimos 20 anos. Colheram-se, durante oito meses, e dentro de uma mesma área predeterminada em cada propriedade, amostras para determinar as concentrações de Ca, P, Mg, Na e S. Verificou-se efeito do mês de coleta sobre todos os minerais analisados. Foram constatados teores suficientes de Ca e Mg para as categorias de bovinos de corte menos exigentes. Os teores de Mg são deficientes para vacas em gestação e lactação e os teores de Ca são deficientes para terneiros. Por outro lado, os teores de P, Na e S apresentaram-se abaixo das exigências mínimas para as categorias de bovinos de corte avaliadas.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.848
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.254
Teacher spread0.232 · 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 teacher head, not a consensus.

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

Citations14
Published2006
Admission routes1
Has abstractyes

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