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Record W6884662119 · doi:10.11575/prism/35965

Integrating Renewable Energy In Alberta: An Examination Of Electricity Cost Impact Of The Proposed Climate Leadership Plan

2016· other· en· W6884662119 on OpenAlexaboutno aff

Bibliographic record

VenuePRISM (University of Calgary) · 2016
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsElectricityRenewable energyBaseline (sea)Greenhouse gasElectricity retailingElectricity generationClimate changeCarbon priceElectric power industryPlan (archaeology)Electricity market

Abstract

fetched live from OpenAlex

Alberta’s Climate Leadership Plan is perhaps the most ambitious undertaking for curbing carbon emissions and promoting renewables in the province. This study evaluates cost of electricity generated under the proposed plan where 30% of the electricity is sourced from renewables, and estimates the emission reduction against a business-as-usual scenario. The feed-in cost of electricity generated is computed by working out asset mix, electricity output and transmission costs under different scenarios. Assuming that the existing renewable facilities continue to generate electricity at current levels, the study reveals the Climate Leadership plan’s carbon mitigation target can be met by sourcing 30% of the electricity from wind. Meeting the emissions reductions target would result in 11% to 60% increase in the cost of electricity generated as compared to the Baseline scenario, depending on whether it is sourced from wind or PV respectively. Under the Climate Leadership plan GHG emissions are projected to reduce by 18 megatonnes vis-à-vis baseline scenario.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.022
GPT teacher head0.224
Teacher spread0.202 · 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 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
Published2016
Admission routes1
Has abstractyes

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