Bibliographic record
Abstract
The Southeast Regional Carbon Sequestration Partnership's (SECARB) Phase I program focused on promoting the development of a framework and infrastructure necessary for the validation and commercial deployment of carbon sequestration technologies. The SECARB program, and its subsequent phases, directly support the Global Climate Change Initiative's goal of reducing greenhouse gas intensity by 18 percent by the year 2012. Work during the project's two-year period was conducted within a ''Task Responsibility Matrix''. The SECARB team was successful in accomplishing its tasks to define the geographic boundaries of the region; characterize the region; identify and address issues for technology deployment; develop public involvement and education mechanisms; identify the most promising capture, sequestration, and transport options; and prepare action plans for implementation and technology validation activity. Milestones accomplished during Phase I of the project are listed below: (1) Completed preliminary identification of geographic boundaries for the study (FY04, Quarter 1); (2) Completed initial inventory of major sources and sinks for the region (FY04, Quarter 2); (3) Completed initial development of plans for GIS (FY04, Quarter 3); (4) Completed preliminary action plan and assessment for overcoming public perception issues (FY04, Quarter 4); (5) Assessed safety, regulatory and permitting issues (FY05, Quarter 1); (6) Finalized inventory of major sources/sinks and refined GIS algorithms (FY05, Quarter 2); (7) Refined public involvement and education mechanisms in support of technology development options (FY05, Quarter 3); and (8) Identified the most promising capture, sequestration and transport options and prepared action plans (FY05, Quarter 4).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.090 | 0.029 |
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".