Department of Energy's regional carbon sequestration partnership initiative: Update on validation and development phases
Bibliographic record
Abstract
Elsevier use only: Received date here; revised date here; accepted date here The U.S. Department of Energy (DOE) is the lead federal agency for the development and deployment of carbon sequestration technologies. The Regional Carbon Sequestration Partnerships (RCSPs) are the mechanism DOE utilizes to prove the technology and to develop human capital, stakeholder networks, information for regulatory policy, best practices documents and training to work toward the commercialization of carbon capture and storage (CCS). The RCSPs are tasked with determining the most suitable technologies, regulations, and2 Rodosta et al. / Energy Procedia 00 (2010) 000–000 infrastructure for carbon capture, transport, and storage in their respective geographic areas of responsibility. The seven partnerships include more than 400 state agencies, universities, national laboratories, private companies, and environmental organizations, spanning 43 states and four Canadian provinces.
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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 | 0.096 | 0.070 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.009 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".