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Record W6959751891 · doi:10.11575/prism/30123

Alberta's Energy Future in Carbon Capture and Storage: A Comparative Analysis of CCS Legislation

2013· other· en· W6959751891 on OpenAlexaboutno aff

Bibliographic record

VenueOpen MIND · 2013
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicGenetic and Environmental Crop Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationGovernment (linguistics)LiabilityStewardship (theology)Order (exchange)Best practiceCarbon capture and storage (timeline)PaymentState (computer science)Climate change mitigation

Abstract

fetched live from OpenAlex

The interest in climate change policy by governments is greater than it has ever been before. With two Carbon Capture and Storage (CCS) projects set to be in operation in Alberta by 2015, it is a good time to examine and evaluate the legislation that these projects will be operating under. By undertaking a qualitative cross-jurisdictional analysis, this report determines the best practices that exist within the written CCS legislation of other states when compared to Alberta’s law. By examining CCS legislation passed in Wyoming, Kansas, Montana and the States of Victoria and Queensland in Australia an understanding of the positive and negative elements of the written CCS legislation in Alberta is formed. In order to understand where the Albertan legislation fails, the report address three policy problems that currently sit within The Carbon Capture and Storage Amendments Act. These are: 1. Payments into the Post Closure Stewardship Fund 2. Monitoring Measurement and Verification (MMV) Plans 3. Time frames for the transfer of liability The report concludes that Kansas’ coverage of fees is preferable to look at for CCS in Alberta, the State of Victoria has the most comprehensive MMV plans to learn from and, that Montana’s time frames for the transfer of liability will ensure a smoother transition once liability is taken over by the government. Knowledge sharing from other jurisdictions is vital to determine where Alberta’s laws fall flat. In order to ensure that legal coverage for the sequestration of CO2 in Alberta is undertaken properly it is important that the Government of Alberta correct these policy issues in order to ensure a well-functioning legal environment is in place.

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)0.003
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.608

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
Science and technology studies0.0060.003
Scholarly communication0.0060.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.020
GPT teacher head0.232
Teacher spread0.211 · 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
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
Published2013
Admission routes1
Has abstractyes

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