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Record W2146931523

International Symposium on Site Characterization for CO2 Geological Storage

2006· article· en· W2146931523 on OpenAlexfundno aff
Chin‐Fu Tsang

Bibliographic record

VenueUniversity of North Texas Digital Library (University of North Texas) · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsnot available
FundersLawrence Berkeley National LaboratoryNational Energy Technology LaboratoryLawrence Livermore National LaboratoryBundesministerium für Bildung und ForschungEuropean CommissionFord Motor CompanyPetroleum Technology Research CentreU.S. Department of EnergyU.S. Environmental Protection AgencyOffice of Fossil EnergyDeutsche Forschungsgemeinschaft
KeywordsCharacterization (materials science)GeologyEnvironmental scienceEarth scienceNanotechnologyMaterials science
DOInot available

Abstract

fetched live from OpenAlex

Several technological options have been proposed to stabilize atmospheric concentrations of CO{sub 2}. One proposed remedy is to separate and capture CO{sub 2} from fossil-fuel power plants and other stationary industrial sources and to inject the CO{sub 2} into deep subsurface formations for long-term storage and sequestration. Characterization of geologic formations for sequestration of large quantities of CO{sub 2} needs to be carefully considered to ensure that sites are suitable for long-term storage and that there will be no adverse impacts to human health or the environment. The Intergovernmental Panel on Climate Change (IPCC) Special Report on Carbon Dioxide Capture and Storage (Final Draft, October 2005) states that ''Site characterization, selection and performance prediction are crucial for successful geological storage. Before selecting a site, the geological setting must be characterized to determine if the overlying cap rock will provide an effective seal, if there is a sufficiently voluminous and permeable storage formation, and whether any abandoned or active wells will compromise the integrity of the seal. Moreover, the availability of good site characterization data is critical for the reliability of models''. This International Symposium on Site Characterization for CO{sub 2} Geological Storage (CO2SC) addresses the particular issue of site characterization and site selection related to the geologic storage of carbon dioxide. Presentations and discussions cover the various aspects associated with characterization and selection of potential CO{sub 2} storage sites, with emphasis on advances in process understanding, development of measurement methods, identification of key site features and parameters, site characterization strategies, and case studies.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.997

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 communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.008
GPT teacher head0.169
Teacher spread0.161 · 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.

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

Citations1
Published2006
Admission routes1
Has abstractyes

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