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Record W2001028608 · doi:10.1016/j.egypro.2009.02.057

A national look at carbon capture and storage—National carbon sequestration database and geographical information system (NatCarb)

2009· article· en· W2001028608 on OpenAlexaboutno aff
Timothy R. Carr, Asif Iqbal, Nick Callaghan, Dana-Adkins-Heljeson, Kurt Look, Shawn Saving, Nelson Ken

Bibliographic record

VenueEnergy Procedia · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsnot available
FundersU.S. Geological Survey
KeywordsGeospatial analysisCarbon sequestrationDatabaseGeographic information systemCarbon capture and storage (timeline)Computer scienceGeographyRemote sensingClimate change

Abstract

fetched live from OpenAlex

The US Department of Energy’s Regional Carbon Sequestration Partnerships (RCSPs) are responsible for generating geospatial data for the maps displayed in the Carbon Sequestration Atlas of the United States and Canada . Key geospatial data (carbon sources, potential storage sites, transportation, land use, etc.) are required for the Atlas, and for efficient implementation of carbon sequestration on a national and regional scale. The National Carbon Sequestration Database and Geographical Information System (NatCarb) is a relational database and geographic information system (GIS) that integrates carbon storage data generated and maintained by the RCSPs and various other sources. The purpose of NatCarb is to provide a national view of the carbon capture and storage potential in the U.S. and Canada. The digital spatial database allows users to estimate the amount of CO 2 emitted by sources (such as power plants, refineries and other fossil-fuel-consuming industries) in relation to geologic formations that can provide safe, secure storage sites over long periods of time. The NatCarb project is working to provide all stakeholders with improved online tools for the display and analysis of CO 2 carbon capture and storage data. NatCarb is organizing and enhancing the critical information about CO 2 sources and developing the technology needed to access, query, model, analyze, display, and distribute natural resource data related to carbon management. Data are generated, maintained and enhanced locally at the RCSP level, or at specialized data warehouses, and assembled, accessed, and analyzed in real-time through a single geoportal. NatCarb is a functional demonstration of distributed data-management systems that cross the boundaries between institutions and geographic areas. It forms the first step toward a functioning National Carbon Cyberinfrastructure (NCCI). NatCarb provides access to first-order information to evaluate the costs, economic potential and societal issues of CO 2 capture and storage, including public perception and regulatory aspects. NatCarb online access has been modified to address the broad needs of a spectrum of users. NatCarb includes not only GIS and database query tools for high-end user, but simplified display for the general public using readily available web tools such as Google Earth™and Google Maps™. Not only is NatCarb connected to all the RCSPs, but data are also pulled from public servers including the U.S. Geological Survey-EROS Data Center and from the Geography Network. Data for major CO 2 sources have been obtained from U.S. Environmental Protection Agency (EPA) databases, and data on major coal basins and coalbed methane wells were obtained from the Energy Information Administration (EIA).

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.771
Threshold uncertainty score0.517

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.007
GPT teacher head0.209
Teacher spread0.203 · 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 designTheoretical or conceptual
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

Citations14
Published2009
Admission routes1
Has abstractyes

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