Creating core CCS messages: Focus Group Testing and Peer Review of Questions and Answers from the IEAGHG Weyburn-midale CO2 Monitoring and Storage Project
Bibliographic record
Abstract
The publication in 2012 of Best Practices for Validating CO 2 Geological Storage: Observations and Guidance from the IEAGHG Weyburn-Midale CO 2 Monitoring and Storage Project marked the culmination of 12 years of research at the Weyburn and Midale oilfields in south-eastern Saskatchewan, Canada. From 2000 to 2012, close to 23 million tonnes of carbon dioxide were injected into depleted oil reservoirs during enhanced oil recovery operations (EOR); the measurement/monitoring research conducted with those EOR operations demonstrated that storage in deep geological formations is a safe and effective means of reducing GHG emissions. The wealth of results accumulated and disseminated during the Weyburn-Midale Project (WMP) has been important for CCUS and CCS project managers and researchers alike, but serious public concerns continue worldwide related to the safety of CO 2 underground storage. In late 2012, the Global Carbon Capture and Storage Institute approached the Petroleum Technology Research Centre (managers of the WMP) to produce a “core messages” booklet that would offer answers to questions that persistently arise from the general public about carbon capture and storage, by incorporating the scientific information garnered over the life of the WMP. The booklet, What Happens When CO 2 is Stored Underground: Q&A from the IEAGHG Weyburn-Midale CO 2 Monitoring and Storage Project was published in 2013 and engaged several steps in its development including a review of existing frequently asked questions on CCS; identification of additional questions and answers using WMP results; community focus group analyses of a completed draft of the booklet; a peer review of the booklet and the focus group responses by CCS communications experts; and, finally, a redrafted final publication.
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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 | 0.234 | 0.473 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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".