Carbon Capture and Sequestration: A Potential "Win-Win" for the Oil Industry and the Public
Bibliographic record
Abstract
Public Policy Focus - The status of carbon capture and sequestration. In 1972, the first commercial carbon dioxide (CO2) flood project in the world began with the injection of CO2 into the Scurry Area Canyon Reef Operators Committee (SACROC) unit in the Permian Basin in Scurry County, Texas. The goal was simple: To arrest declining oil production and recover bypassed reserves. Today, nearly 40 years later, CO2 injection is being considered on a much wider scale, and for a different purpose altogether: To help arrest an increase in the average surface temperature of the planet. CO2, among other gases such as methane and nitrous oxide, is a “greenhouse gas,” a gas that traps heat in the Earth’s atmosphere by absorbing and emitting radiation within the thermal infrared range, causing a greenhouselike warming effect. The presence of greenhouse gases in Earth’s atmosphere is vital, for without them, Earth’s surface would be on average about 59°F colder than at present. CO2 is also a key ingredient that nourishes plant life through photosynthesis.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.011 | 0.005 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".