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Record W2913846259 · doi:10.21577/1984-6835.20180118

Nitrogen Cycling in Tropical Forests and Eucalyptus Plantations in Brazil in the Anthropocene

2018· article· en· W2913846259 on OpenAlexaff
Jacqueline J. N. da Silva, William Zamboni de Mello, Renato de Aragão Ribeiro Rodrigues, Bruno José Rodrígues Alves, Patricia Alexandre de Souza, Marcela Cardoso Guilles da Conceição

Bibliographic record

VenueRevista Virtual de Química · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and biological studies
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsAnthropoceneEucalyptusCyclingAgroforestryNitrogen cycleTropicsNitrogenEnvironmental scienceGeographyForestryEcologyBiologyChemistry

Abstract

fetched live from OpenAlex

The nitrogen is a macronutrient essential for the functioning of the metabolism of living beings.However, due to the changes that the planet has been passing in the Anthropocene, the nitrogen cycling has been altered.Deforestation combined with changes in land use are primarily responsible for the change in their cycling.Emissions of greenhouse gases such as N2O were increased due to this deforestation and inadequate soil management practices, and this contributed to the fact that these changes in nitrogen cycling occurred.Considering the importance of nitrogen and the changes that it has undergone in the last decades, this work of revision aims to describe the role of nitrogen and the changes in its cycling due to the processes of land use change that occurred in the Anthropocene in forest areas tropical and eucalyptus plantations in Brazil.

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 score0.115
Threshold uncertainty score0.228

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 communication0.0000.000
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 head0.013
GPT teacher head0.271
Teacher spread0.258 · 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

Citations7
Published2018
Admission routes1
Has abstractyes

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