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Record W2013004507 · doi:10.5380/rsa.v9i2.10942

ALOCAÇÃO DE BIOMASSA EM PLANTAS DE BAMBU EM RESPOSTA A ADUBAÇÃO MINERAL

2008· article· pt· W2013004507 on OpenAlexaff
Dagmar Alves de Oliveira, Egídio Bezerra Neto, C. W. A. Nascimento, Michelangelo Bezerra Fernandes, Tereza Cristina da Silva, Rodrigo Alves de Oliveira

Bibliographic record

VenueScientia Agraria · 2008
Typearticle
Languagept
FieldAgricultural and Biological Sciences
TopicBamboo properties and applications
Canadian institutionsCascades (Canada)
Fundersnot available
KeywordsHorticultureChemistryRandomized block designBiology

Abstract

fetched live from OpenAlex

O presente estudo teve como o objetivo avaliar a influência da adubação mineral na alocação de biomassa nas raízes, colmo e folhas de bambu cultivadas em casa de vegetação. O solo é classificado como Neossolo Quartzarenico, foi adubado com as doses equivalentes a 0, 20, 40, 80 e 120 kg ha-1 de nitrogênio e 0, 10, 40, 80 e 100 kg ha-1 de fósforo e potássio, respectivamente. O delineamento experimental foi em blocos casualizados, em um esquema fatorial com quatro repetições. As plantas de bambu foram cultivadas durante 120 dias em casa de vegetação. Após este período as plantas foram coletadas e determinadas a biomassa das folhas, colmo, raízes e biomassa total. A maior produção de biomassa seca total foi obtida nas doses equivalentes a 120, 10 e 100 kg ha-1 de NPK. A maior produção da biomassa seca das folhas foi obtida com as doses equivalentes a 80, 10 e 100 kg ha-1 NPK, respectivamente. No colmo com as doses equivalentes a 120, 40 e 100 kg ha-1 NPK, respectivamente. E a maior produção nas raízes foi obtida respectivamente com as doses equivalente a e 80, 10 e 100 kg ha-1 de NPK. A adubação com N e K proporcionou aumento na produção da biomassa total das plantas de bambu.

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 categoriesScience and technology studies, 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 score0.681
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.039
GPT teacher head0.233
Teacher spread0.195 · 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

Citations2
Published2008
Admission routes1
Has abstractyes

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