International Symposium on Site Characterization for CO2 Geological Storage
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".