Southeast Regional Carbon Sequestration Partnership Phase III Overview of Accomplishments (SECARB Phase III Final Report)
Bibliographic record
Abstract
The Southeast Regional Carbon Sequestration Program (SECARB) is a carbon management program established in 2003 and managed by the Southern States Energy Board (SSEB). SECARB is one of seven regional carbon sequestration partnerships formed by the Department of Energy (DOE). The seven partnerships form a national network of more than 400 organizations covering 43 states and four Canadian provinces with expertise in the areas of carbon capture, transportation, and storage. The SECARB program was funded by DOE and cost-sharing partners. The primary goal of SECARB was to identify major sources of carbon emissions, characterize the geology of a 13-state region, determine the most promising options for commercial deployment of carbon dioxide (CO2) sequestration technologies in the South, and validate the technology options through carefully executed field testing through 2017. This report summarizes significant Phase III accomplishments and is organized by task as established within the SECARB Phase III Statement of Project Objectives (SOPO). This document does not provide an exhaustive overview of individual tasks. Rather, this report provides an overview of programmatic accomplishments and a timeline of events. Where applicable, hyperlinks to specific project deliverables are provided.
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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 | 0.017 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.034 | 0.035 |
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".