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Record W2330578565 · doi:10.5897/ajar2013.7293

Sources and rates of nitrogen in summer corn under no-tillage on winter cover crops

2014· article· en· W2330578565 on OpenAlexaff
Werncke Ivan, Nelson Melegari de Souza Samuel, Bassegio Doglas, Ferreira Santos Reginaldo, Pereira Dias Patricia, Deonir Secco, Gurgacz Flvio, Aparecido Bariccatti Reinaldo, Cristina Morais Vidal Thais

Bibliographic record

VenueAfrican Journal of Agricultural Research · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsWestern University
Fundersnot available
KeywordsAgronomyCover cropNitrogenTillageRaphanusNutrientEnvironmental scienceCropWeedBiologyChemistry

Abstract

fetched live from OpenAlex

Cover crops occupy and protect the soil during winter and also provide nutrients to tropical soils. The aim of this study was to evaluate the effect of sources and levels of nitrogen applied to a summer corn crop cover in succession to cover cropsunder no-tillage. The experimental design consisted of randomized blocks with four replications in a scheme with subdivided plots. The main plot was composed of two crops that preceded corn; common oat (Avena strigosa Schreb.) and forage turnip (Raphanus sativus), and a winter fallow area (weed). The subplot consisted of two nitrogen sources (urea and ammonium sulphate), and the splits of each subplot were constituted by four rates of nitrogen (0, 30, 60 and 120 kg ha-1). The following production components were analyzed: ear diameter, kernel rows per ear, mass of 1000 grains and grain yield. Corn grown after oat presented responses to nitrogen fertilization for mass of 100 grains and hence to grain yield. Key words:  Zea mays, nitrogen fertilization, urea, ammonium sulphate.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.491
Threshold uncertainty score0.270

Codex and Gemma teacher scores by category

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

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 head0.066
GPT teacher head0.310
Teacher spread0.245 · 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.

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
Published2014
Admission routes1
Has abstractyes

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