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Fertilidade química de um substrato tratado com lodo de esgoto e composto de resíduos domésticos

2010· article· pt· W2085349912 on OpenAlexaff
Rodrigo Studart Corrêa, Lucas C. R. Silva, Gustavo Macêdo de Mello Baptista, Perseu F. Santos

Bibliographic record

VenueRevista Brasileira de Engenharia Agrícola e Ambiental · 2010
Typearticle
Languagept
FieldAgricultural and Biological Sciences
TopicGrowth and nutrition in plants
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsChemistry

Abstract

fetched live from OpenAlex

O aproveitamento de resíduos urbanos como fontes de matéria orgânica e nutrientes contribui para diminuir a pressão das sociedades modernas sobre o meio ambiente. Por outro lado, a incorporação de matéria orgânica é um meio de se criarem condições edáficas para o estabelecimento de plantas em solos degradados e substratos expostos. Este trabalho visou avaliar a fertilidade e a cobertura vegetal (Paspalum notatum var. saurae Parodi) de um substrato exposto à superfície, tratado com doses crescentes (0 - 76 Mg ha-1, base seca) de lodo de esgoto ou composto de resíduos domésticos. Os resultados indicam que o lodo de esgoto foi capaz de aumentar a CTC e as concentrações de N, P e Zn no substrato enquanto não houve incrementos significativos desses nutrientes no substrato tratado com o composto de resíduos domésticos. A cobertura vegetal do substrato variou de 68 a 96% nos tratamentos com lodo (resposta assintótica) e entre 22 e 67% nos tratamentos com composto (resposta linear), de acordo com a dose aplicada. Valores de CTC e concentrações de N, P e Zn explicaram 94% da variação da cobertura vegetal sobre a superfície da área.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.017
GPT teacher head0.251
Teacher spread0.235 · 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

Citations13
Published2010
Admission routes1
Has abstractyes

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