MétaCan
Menu
Back to cohort
Record W4380029001 · doi:10.54254/2755-2721/3/20230348

Comparative analysis of renewable energy

2023· article· en· W4380029001 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueApplied and Computational Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicEnergy Load and Power Forecasting
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRenewable energyWind powerEnvironmental economicsClimate changeEnergy transitionNatural resource economicsNatural resourceProcess (computing)Environmental resource managementBusinessEnvironmental planningEnvironmental scienceComputer scienceEngineeringEconomicsPolitical scienceEcology

Abstract

fetched live from OpenAlex

Our current reliance on non-renewable sources of energy has put a strain on the limitations of our planet and its natural resources. The purpose of this study was to comparatively assess the various physical and socioeconomic factors affecting a city and its residents ability to effectively transition to renewable energy sources such as solar or wind energy. Using climate datasets to assess the potential of both wind and solar energy for Edmonton, AB, and Columbus, OH. the researcher paired these findings with assessments of urban development, socioeconomic factors present in both cities to fully understand the current challenges we face in transitioning to renewable energy. The findings indicate that while the area of land needed to supply Edmonton with energy from 100% renewable sources would be vast (1815 km2; 6412 Wind Turbines), it would be possible to accomplish. A change as large as this cannot be made instantaneously and cities will face various challenges in this process, but it is crucial to make this transition in order to become a more sustainable society and live more harmoniously with the natural environment.

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.

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 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 score0.421
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.203
Teacher spread0.193 · 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