CCS AS ONE OF the CO2 EMISSION REDUCTION METHODS
Bibliographic record
Abstract
Information presented in the article allows us to introduce one of the ways of reducing anthropogenic greenhouse gas emissions responsible for the temperature increase and climate change. This is the technology of capture and underground storage of carbon dioxide in geologic structures (Carbon Capture and Storage/Sequestration – CCS). Most of the large-scale CCS projects (i.e. capture and storage of an order of magnitude of 1 million tonnes of CO2 per year) operate in the United States and Canada. Many of them are associated with the use of CO2 captured from the industrial processes for the enhanced oil recovery (EOR). The presented examples of projects are: Boundary Dam Integrated Carbon Capture and Sequestration Demonstration Project (Canada), Great Plains Synfuels and Weyburn-Midale Project (Canada), and Kemper County IGCC Project (United States). CCS projects are crucial for demonstrating the technological readiness and reduce the cost of wider commercial implementation of capture and geological storage of CO2. The status of the projects on geological storage of CO2 in 2015 is 15 large-scale CCS projects operating around the world, and 7 projects in execution.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".