The Midwest Regional Carbon Sequestration Partnership (MRCSP)
Bibliographic record
Abstract
This final report summarizes the Phase I research conducted by the Midwest regional Carbon Sequestration Partnership (MRCSP). The Phase I effort began in October 2003 and the project period ended on September 31, 2005. The MRCSP is a public/private partnership led by Battelle with the mission of identifying the technical, economic, and social issues associated with implementation of carbon sequestration technologies in its seven state geographic region (Indiana, Kentucky, Maryland, Michigan, Ohio, Pennsylvania, and West Virginia) and identifying viable pathways for their deployment. It is one of seven partnerships that together span most of the U.S. and parts of Canada that comprise the U.S. Department of Energy's (DOE's) Regional Carbon Sequestration Program led by DOE's national Energy Technology Laboratory (NETL). The MRCSP Phase I research was carried out under DOE Cooperative Agreement No. DE-FC26-03NT41981. The total value of Phase I was $3,513,513 of which the DOE share was $2,410,967 or 68.62%. The remainder of the cost share was provided in varying amounts by the rest of the 38 members of MRCSP's Phase I project. The next largest cost sharing participant to DOE in Phase I was the Ohio Coal Development Office within the Ohio Air Quality Development Authority (OCDO). OCDO's contribution was $100,000 and was contributed under Grant Agreement No. CDO/D-02-17. In this report, the MRCSP's research shows that the seven state MRCSP region is a major contributor to the U. S. economy and also to total emissions of CO2, the most significant of the greenhouse gases thought to contribute to global climate change. But, the research has also shown that the region has substantial resources for sequestering carbon, both in deep geological reservoirs (geological sequestration) and through improved agricultural and land management practices (terrestrial sequestration). Geological reservoirs, especially deep saline reservoirs, offer the potential to permanently store CO2 for literally 100s of years even if all the CO2 emissions from the region's large point sources were stored there, an unlikely scenario under any set of national carbon emission mitigation strategies. The terrestrial sequestration opportunities in the region have the biophysical potential to sequester up to 20% of annual emissions from the region's large point sources of CO2. This report describes the assumptions made and methods employed to arrive at the results leading to these conclusions. It also describes the results of analyses of regulatory issues in the region affecting the potential for deployment of sequestration technologies. Finally, it describes the public outreach and education efforts carried out in Phase I including the creation of a web site dedicated to the MRCSP at www.mrcsp.org.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.038 | 0.010 |
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".