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Record W2902639400 · doi:10.1109/pvsc.2018.8547671

Efficient, Real-Time Global Spectral and Broadband Irradiance Acquisition

2018· article· en· W2902639400 on OpenAlexaff
Viktar Tatsiankou, Karin Hinzer, Henry Schriemer, Patrick McVey-White, Richard Beal

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsSpectra Energy (Canada)University of Ottawa
Fundersnot available
KeywordsSpectroradiometerPyranometerIrradianceBroadbandStandard deviationRemote sensingPhysicsOpticsEnvironmental scienceGeographyMathematicsStatisticsReflectivity

Abstract

fetched live from OpenAlex

Two global solar spectral irradiance meters (SolarSIM-Gs) were deployed and tested at the National Renewable Energy Laboratory in Golden, USA from 18 September to 6 October 2017. The instruments were installed in the global horizontal orientation at the Solar Radiation Research Laboratory and their measurements were compared against colocated secondary reference spectroradiometers and secondary standard pyranometers. The SolarSIM-Gs' spectral global horizontal irradiance (GHI) accuracy was shown to be2and 5.27, 5.65 W/m2, respectively, for over 10,000 analyzed data points.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.002

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 head0.007
GPT teacher head0.244
Teacher spread0.236 · 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 designBench or experimental
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

Citations12
Published2018
Admission routes1
Has abstractyes

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