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Record W4300598127 · doi:10.2172/1874349

Storage Capacity and Regional Implications for Large-Scale Storage in the Basal Cambrian System

2014· report· en· W4300598127 on OpenAlexaboutno aff
Wesley Peck, Guoxiang Liu, Robert Klenner, Megan Grove, Charles D. Gorecki, Edward N. Steadman, John A. Harju

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsResource (disambiguation)Environmental scienceEarth scienceGeographyHydrology (agriculture)Geology

Abstract

fetched live from OpenAlex

A binational effort, between the United States and Canada, characterized the lowermost saline system in the Williston and Alberta Basins of the northern Great Plains–Prairie region of North America in the United States and Canada. This 3-year project was conducted with the goal of determining the potential for geologic storage of carbon dioxide (CO2 ) in rock formations of the 517,000 sq mi Cambro-Ordovician Saline System (COSS). This project was led on the U.S. side by the Energy & Environmental Research Center (EERC) through the Plains CO2 Reduction (PCOR) Partnership and on the Canadian side by Alberta Innovates Technology Futures (AITF). The project characterized the COSS using well log and core data from three states and three provinces and determined its storage potential by creating a heterogeneous 3-D model and determined the effects of CO2 storage in this system using dynamic simulation. The area underlain by the COSS includes several large CO2 sources that each emits more than 1 Mt CO2 /year. Assuming that each of these sources will target the COSS for the storage of their CO2, the primary questions addressed by this study are 1) what is the CO2 storage resource of the COSS, 2) how many years of current CO2 emissions will it be capable of storing, and 3) what will be required and what will be the effect of injecting 104 Mt/yr of CO2 into the COSS?

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.912
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

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

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 head0.049
GPT teacher head0.293
Teacher spread0.245 · 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 teacher head, 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
Published2014
Admission routes1
Has abstractyes

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