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Record W2896136286 · doi:10.14393/bj-v34n5a2018-39485

Changes in past global solar radiation based on climate models and remote sensing in the state of Rio de Janeiro, Brazil

2018· article· en· W2896136286 on OpenAlexaboutno aff
Carolina Souza Leite de Jesus, Rafael Coll Delgado, Marcos Gervásio Pereira, Leonardo Paula de Souza, Carlos Antônio da Silva, Larissa Pereira Ribeiro Teodoro, Tays Silva Batista, Paulo Eduardo Teodoro

Bibliographic record

VenueBioscience Journal · 2018
Typearticle
Languageen
FieldComputer Science
TopicSolar Radiation and Photovoltaics
Canadian institutionsnot available
FundersUniversidade Federal de Mato Grosso do SulCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsEnvironmental scienceRemote sensingGeographyClimate changeState (computer science)RadiationMeteorologyClimatologyAtmospheric sciencesPhysicsGeologyComputer scienceEcologyBiology

Abstract

fetched live from OpenAlex

The objective of this study was to perform a temporal and spatial analysis of the changes in the past global solar radiation based on climate models and remote sensing data in the State of Rio de Janeiro, Brazil for the baseline period (1961-1990). Data from two climate models - the Canadian Centre for Climate Modelling and Analysis and Geophysical Fluid Dynamic Laboratory, were used for the A1B intermediate scenario, data from Conventional Weather Stations and orbital sensor Moderate Resolution Imaging Spectroradiometer (MODIS) MODIS Land Cover Type (MCD12Q1). The results of the Spatial Dependence Degree indicate that the best model to represent the global solar radiation is CCCMA-Exponential dry 70.01 and rainy 0.21 respectively. It was possible to verify that in places where the areas are occupied by forests there was reduction of global solar radiation for both dry and rainy periods of approximately 13 MJ m-2d-1. These results indicate that these forest areas can function as islands of freshness, while maintaining the thermal comfort balanced. It was concluded that the dry period had the highest values of solar radiation compared to the rainy (57%), which can be justified by the occurrence of fires in Rio de Janeiro.

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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.907
Threshold uncertainty score0.226

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.022
GPT teacher head0.279
Teacher spread0.257 · 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 designOther design
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
Published2018
Admission routes1
Has abstractyes

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