PLAINS CO2 REDUCTION (PCOR) PARTNERSHIP
Bibliographic record
Abstract
During the period of October 1, 2003, through September 30, 2005, the Plains CO2 Reduction (PCOR) Partnership, identified geologic and terrestrial candidates for near-term practical and environmentally sound carbon dioxide (CO2) sequestration demonstrations in the heartland of North America. The PCOR Partnership region covered nine states and three Canadian provinces. The validation test candidates were further vetted to ensure that they represented projects with (1) commercial potential and (2) a mix that would support future projects both dependent and independent of CO2 monetization. This report uses the findings contained in the PCOR Partnership's two dozen topical reports and half-dozen fact sheets as well as the capabilities of its geographic information system-based Decision Support System to provide a concise picture of the sequestration potential for both terrestrial and geologic sequestration in the PCOR Partnership region based on assessments of sources, sinks, regulations, deployment issues, transportation, and capture and separation. The report also includes concise action plans for deployment and public education and outreach as well as a brief overview of the structure, development, and capabilities of the PCOR Partnership. The PCOR Partnership is one of seven regional partnerships under Phase I of the U.S. Department of Energy National Energy Technology Laboratory's Regional Carbon Sequestration Partnership program. The PCOR Partnership, comprising 49 public and private sector members, is led by the Energy & Environmental Research Center at the University of North Dakota. The international PCOR Partnership region includes the Canadian provinces of Alberta, Saskatchewan, and Manitoba and the states of Montana (part), Wyoming (part), North Dakota, South Dakota, Nebraska, Missouri, Iowa, Minnesota, and Wisconsin.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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".