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Record W2752659327 · doi:10.1063/1.5001451

Deployment and early results from the CanSIM (Canadian Solar Spectral Irradiance Meter) network

2017· article· en· W2752659327 on OpenAlexafffundabout
Viktar Tatsiankou, Karin Hinzer, Henry Schriemer, Patrick McVey-White, Richard Beal

Bibliographic record

VenueAIP conference proceedings · 2017
Typearticle
Languageen
FieldComputer Science
TopicSolar Radiation and Photovoltaics
Canadian institutionsSpectra Energy (Canada)University of Ottawa
FundersEnvironment and Climate Change CanadaPublic Works and Government Services CanadaGovernment of Canada
KeywordsPyranometerIrradianceSpectroradiometerEnvironmental scienceRemote sensingSolar irradianceAtmospheric sciencesMeteorologyPhysicsGeographyOpticsReflectivity

Abstract

fetched live from OpenAlex

Three of seven stations have been deployed as part of the Canadian Solar Spectral Irradiance (CanSIM) network situated in Ottawa, Varennes and Egbert to measure long term spectral variation of the direct normal (DNI) and global horizontal irradiances (GHI) across the country. Every station is equipped with a solar tracker, SolarSIM-D2+, SolarSIM-G+, and SR20 pyranometer, reporting the spectral DNI, GHI, diffuse horizontal irradiance (DHI) and aerosol optical depth in the 280–4000 nm range, broadband DNI, GHI, and DHI, atmospheric total column ozone and water vapour amounts. The spectral GHI as measured by the SolarSIM-G+ was within 5% as compared to EKO MS-700 spectroradiometer in 350–1050 nm range on 17 March 2017. The difference in the GHI as reported by SolarSIM-G+ and SR20 pyranometer from all stations was within 2% on 14 April 2017. Furthermore, on this day, the daily GHI sum for the Ottawa, Varennes, and Egbert stations was 7.01, 6.95, and 7.11 kWh/m2, respectively, while the daily DNI sum was 10.65, 10.86, 10.04 kWh/m2, respectively.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.000
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 head0.032
GPT teacher head0.238
Teacher spread0.206 · 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

Citations5
Published2017
Admission routes3
Has abstractyes

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