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Record W3128331301

Greening the grid : powering Alberta's future with renewable energy

2009· article· en· W3128331301 on OpenAlexaboutno aff
John Bell, Tim Weis

Bibliographic record

VenueOSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2009
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsnot available
Fundersnot available
KeywordsRenewable energyElectricityElectricity generationNuclear powerEnvironmental economicsWind powerEnergy developmentNatural resource economicsBusinessEngineeringEconomicsPower (physics)
DOInot available

Abstract

fetched live from OpenAlex

The Government of Alberta released a statement in its 2008 provincial energy strategy that alternative and renewable energy sources will play a growing role in the province's energy future. This report provided an examination of the extent to which cleaner alternatives to coal, nuclear and other non-renewable resources could be deployed to meet Alberta's electricity consumption over the next 20 years, which is expected to be almost twice the current level of consumption. This report also provided background information on electricity generation in Alberta; a history of electricity in Alberta and electricity in Alberta today; and projecting future needs. The impacts of electricity generation were also presented as they relate to greenhouse gases; other pollution; water use; land use; flora and fauna; employment; and cost. Cleaning Alberta's grid from the perspective of improved efficiency was also examined. Specific renewable energy sources and their technological descriptions that were analysed included wind power; hydro; biomass; geothermal electricity; cogeneration for industry and buildings; recovered industrial energy; micropower; and virtual power plants. Several scenarios were offered, such as business as usual; pale green scenario; and the green scenario. It was recommended that the Government of Alberta assemble a task force or expert panel, analogous to those that have already been assembled to look at nuclear energy and carbon capture and storage, to examine the best ways of promoting renewable electricity. 23 tabs., 44 figs., 1 appendix.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.068
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.006
Science and technology studies0.0030.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0260.003

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 head0.007
GPT teacher head0.225
Teacher spread0.218 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations23
Published2009
Admission routes1
Has abstractyes

Explore more

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