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Record W2052479962 · doi:10.1063/1.4897085

Solar resource assessment with a solar spectral irradiance meter

2014· article· en· W2052479962 on OpenAlexaffabout
Viktar Tatsiankou, Karin Hinzer, Aaron Muron, Joan E. Haysom, Henry Schriemer, Stefan Myrskog

Bibliographic record

VenueAIP conference proceedings · 2014
Typearticle
Languageen
FieldComputer Science
TopicSolar Radiation and Photovoltaics
Canadian institutionsMorgan Solar (Canada)University of Ottawa
Fundersnot available
KeywordsIrradianceSpectroradiometerEnvironmental scienceSolar irradianceRemote sensingMetreSolar energySolar ResourceMeteorologyOpticsReflectivityEngineeringPhysicsGeographyElectrical engineering

Abstract

fetched live from OpenAlex

The SSIM prototype was designed at the University of Ottawa as a cost-effective alternative to a field spectrora-diometer. The instrument was installed at the University of Ottawa’s CPV testing facility in September, 2013, collecting the environmental and spectral data from October, 2013 to March, 2014. The SSIM’s performance was compared against an ASD field spectroradiometer and an Eppley pyrheliometer during a six month study. It was observed that the SSIM can accurately reproduce the solar spectrum and the direct normal irradiance. The mean difference between the SSIM and the Eppley pyrheliometer was within ±1.5% for cloudless periods in October, 2013. However, bandpass filter degradation and moisture ingress limited the long term performance of the device.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.883
Threshold uncertainty score0.893

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 studies0.0000.000
Scholarly communication0.0010.001
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 head0.017
GPT teacher head0.240
Teacher spread0.223 · 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 designTheoretical or conceptual
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

Citations4
Published2014
Admission routes2
Has abstractyes

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