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Record W2003696631 · doi:10.1016/j.egypro.2013.06.717

Liability for Sequestered CO2: The Path Forward for Alberta

2013· article· en· W2003696631 on OpenAlexaffabout
Mike Fernandez, Chad Leask, Chris Arnot

Bibliographic record

VenueEnergy Procedia · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsAlberta Energy
Fundersnot available
KeywordsLiabilityLegislationWork (physics)Government (linguistics)BusinessCarbon sequestrationRisk analysis (engineering)Environmental planningEnvironmental economicsCarbon dioxideEngineeringEnvironmental scienceFinancePolitical scienceEconomicsLawChemistry

Abstract

fetched live from OpenAlex

This paper presents the approach being taken by the Province of Alberta (Canada) to assess the site specific risks of carbon dioxide (CO 2 ) sequestration and how the long-term liability associated with such activities will be managed. This paper highlights the benefits Alberta has obtained from the passage of carbon capture and storage (CCS) legislation and summarizes some of the work taking place via the Regulatory Framework Assessment (RFA) to review the specific processes, requirements and performance criteria necessary for the Government of Alberta to manage long-term liability for sequestered CO 2 into the future.

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)0.004
metaresearch head score (Gemma)0.004
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: none
Teacher disagreement score0.086
Threshold uncertainty score0.391

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0040.004
Scholarly communication0.0080.002
Open science0.0030.002
Research integrity0.0050.003
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 head0.010
GPT teacher head0.233
Teacher spread0.223 · 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

Citations1
Published2013
Admission routes2
Has abstractyes

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