MétaCan
Menu
Back to cohort
Record W2886990676 · doi:10.14510/araj.2017.4115

THE IMPORTANCE OF THE AEROSOL MONITORING IN RENEWABLE ENERGY

2017· article· en· W2886990676 on OpenAlexvenueno aff
Delia Calinoiu, G. Trif-Tordai, Ioana Ionel

Bibliographic record

VenueJournal of the American Romanian Academy of Arts and Sciences · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicMaritime Transport Emissions and Efficiency
Canadian institutionsnot available
FundersEuropean Commission
KeywordsAerosolRenewable energyEnvironmental scienceBusinessMeteorologyGeographyEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

The study is relying on detailed physical and optical aerosol properties, data collected from the sun photometer located at Mechanical Engineering Faculty, Politehnica University Timisoara during 2016. Three days with moderate turbidity was selected by analyzing aerosol optical depth (AOD), ngstrm parameter ( ), ngstrm turbidity coefficient ( ) single scattering albedo (SSA) and size distribution. A high AOD (> 0.6), > 0.1, >1.5 and SSA decreases with the wavelengths which means that the atmosphere is loaded with biomass burning aerosol. Also, in this paper renewable energy production was analyzed during selected days with data taken from Transelectrica website, photovoltaic in particular.

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
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
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
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.019
GPT teacher head0.268
Teacher spread0.249 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Romanian Academy of Arts and SciencesSame topicMaritime Transport Emissions and EfficiencyFrench-language works237,207