Summary Report on CO<sub>2</sub> Geologic Sequestration & Water Resources Workshop
Bibliographic record
Abstract
The United States Environmental Protection Agency (EPA) and Lawrence Berkeley National Laboratory (LBNL) jointly hosted a workshop on “CO{sub 2} Geologic Sequestration and Water Resources” in Berkeley, June 1–2, 2011. The focus of the workshop was to evaluate R&D needs related to geological storage of CO{sub 2} and potential impacts on water resources. The objectives were to assess the current status of R&D, to identify key knowledge gaps, and to define specific research areas with relevance to EPA’s mission. About 70 experts from EPA, the DOE National Laboratories, industry, and academia came to Berkeley for two days of intensive discussions. Participants were split into four breakout session groups organized around the following themes: Water Quality and Impact Assessment/Risk Prediction; Modeling and Mapping of Area of Potential Impact; Monitoring and Mitigation; Wells as Leakage Pathways. In each breakout group, participants identified and addressed several key science issues. All groups developed lists of specific research needs; some groups prioritized them, others developed short-term vs. long-term recommendations for research directions. Several crosscutting issues came up. Most participants agreed that the risk of CO{sub 2} leakage from sequestration sites that are properly selected and monitored is expected to be low. However, it also became clear that more work needs to be done to be able to predict and detect potential environmental impacts of CO{sub 2} storage in cases where the storage formation may not provide for perfect containment and leakage of CO{sub 2}–brine might occur.
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 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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.224 | 0.116 |
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".