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Record W2941085628 · doi:10.11575/prism/35961

Effect Of Snow On Solar Photovoltaic Systems In Alberta

2016· article· en· W2941085628 on OpenAlexaboutno aff
Namrata Sheth

Bibliographic record

VenuePRISM (University of Calgary) · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicPhotovoltaic Systems and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsPhotovoltaic systemSnowEnvironmental scienceMeteorologyGeographyEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

Alberta lies in the highest irradiance regions of Canada and has a cold climate which makes it the best candidate to expand its installed solar photovoltaic capacity. Alberta’s Climate Leadership Plan to shut down coal generated electricity is another motivation to develop renewables like solar PV. However, there is a significant amount of snow in Alberta, which may hinder the electricity generation ability of photovoltaic systems. The primary objective of this paper is to find the effect of snow on electricity generation by photovoltaic systems in Alberta. A photovoltaic system is set up in Calgary for the experimental research. The result is there is a 9% loss in energy yield per year due to snow accumulation which is quite an insignificant loss considering the analysis is in the absence of bypass diodes.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.176
Threshold uncertainty score0.859

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 communication0.0000.000
Open science0.0000.000
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 head0.004
GPT teacher head0.180
Teacher spread0.177 · 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 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

Citations1
Published2016
Admission routes1
Has abstractyes

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