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Record W2988471159 · doi:10.34117/bjdv5n10-168

Simulação e análise de potência de placas fotovoltaicas para variações de temperatura e irradiação

2019· article· pt· W2988471159 on OpenAlexaboutno aff
Emmanuel L. C. Saldanha, Mateus C. Machado, Cintia F. F. Carraro, Camila B. Fernandes

Bibliographic record

VenueBrazilian Journal of Development · 2019
Typearticle
Languagept
FieldEnvironmental Science
TopicPhotovoltaic Systems and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsPhysics

Abstract

fetched live from OpenAlex

Seguindo a proposta de metodologia ativa feita pelas discentes na disciplina de fontes renováveis de energia, foi feito a revisão bibliográfica do artigo de Casaro e Martins em 2008 na revista Eletrônica de Potência e com base nos conhecimentos adquiridos e nos dados e métodos propostos foi feito o artigo presente, que desenvolve e explica o método de avaliação de comportamento da potência entregue por uma placa fotovoltaica, submetida a variações de irradiação solar e temperatura, e compara o desempenho de placas solares instaladas em uma determinada região. Para exemplificar este método foi usado a placa JKM315P-72 da Jinko Solar e a CS6-265P da Canadian Solar, ambas submetidas ao clima da região de Angra dos Reis.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.252
Teacher spread0.241 · 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 designSimulation or modeling
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

Citations0
Published2019
Admission routes1
Has abstractyes

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