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Record W2049626102 · doi:10.1016/j.egypro.2014.11.314

Evaluation of large-scale carbon dioxide storage potential in the basal saline system in the Alberta and Williston Basins in North America

2014· article· en· W2049626102 on OpenAlexfundaboutno aff
Guoxiang Liu, Wesley Peck, Jason R. Braunberger, Robert Klenner, Charles D. Gorecki, Edward N. Steadman, John A. Harju

Bibliographic record

VenueEnergy Procedia · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsnot available
FundersAlberta Innovates
KeywordsCarbon dioxideCarbon sequestrationEnvironmental scienceCarbon capture and storage (timeline)Process systemsScale (ratio)Petroleum engineeringTransient (computer programming)Hydrology (agriculture)Environmental engineeringEngineeringGeologyProcess engineeringChemistryComputer scienceGeotechnical engineeringClimate changeGeographyOceanographyCartography

Abstract

fetched live from OpenAlex

The Plains CO2 Reduction (PCOR) Partnership performed a case study on the feasibility of underground carbon dioxide (CO2) storage in the basal saline system of central North America. The calculated volumetric CO2 storage resource potential in this system is 373 Gt. Two dynamic modeling scenarios were designed to address the dynamic CO2 storage capacity and pressure transient. Various strategies were tested including injection well location and spacing, injection optimization, and water extraction during CO2 injection. This study underscores the potential difference in CO2 storage potential between estimates made with volumetric approaches and those made with dynamic methodologies.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.274
Threshold uncertainty score0.550

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
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 designObservational
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

Citations5
Published2014
Admission routes2
Has abstractyes

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