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Record W4402467596 · doi:10.3808/jeil.202400134

Assessing Canada's Renewable Energy Potential under Climate Change through a CMIP6 Multi-Model Ensemble Approach

2022· article· en· W4402467596 on OpenAlexfundaboutno aff
Y. H. Wu, C. Z. Huang, Xingjun Lin

Bibliographic record

VenueJournal of Environmental Informatics Letters · 2022
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsnot available
FundersMitacs
KeywordsRenewable energyClimate changeEnvironmental scienceClimatologyClimate modelMeteorologyGeographyGeologyEngineeringOceanography

Abstract

fetched live from OpenAlex

In this study, Canada's renewable energy potential under future climate scenarios is assessed through an ensemble approach based on the CMIP6 models. The research is focused on the evaluation of hydro, solar, and wind energy potential across different regions in Canada, by taking into account projected changes in surface runoff, solar radiation, and windspeed from 2020 to 2099 under SSP2-4.5 and SSP5-8.5 scenarios. The results indicate significant spatial and temporal variations in renewable energy resources, with a general decline in surface runoff, particularly in Western Canada, which poses challenges for local hydropower generation. Solar energy potential is expected to increase consistently across all regions, with the most significant increases in central and northern Canada. Wind energy shows relatively smaller changes, with a notable increase in Eastern Canada. This comprehensive assessment provides crucial insights for optimizing renewable energy development, and supports Canada’s plan to transform into a low-carbon economy.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score0.926

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 studies0.0010.000
Scholarly communication0.0000.001
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 head0.029
GPT teacher head0.251
Teacher spread0.222 · 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 designSimulation or modeling
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
Published2022
Admission routes2
Has abstractyes

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