Carbon Sequestration: a Potential Source of Income for Farmers
Bibliographic record
Abstract
Concerns regarding climate changes due to human activities have largely increased in the past few years. Many scientists believe that atmospheric build-up of greenhouse gas1 (GHG) concentrations is causing the climate to change (IPCC, 2007a,b). Furthermore, a large number of scientists assert that continuing levels of GHG emissions will lead to substantial future climate change. Carbon dioxide is the largest of the GHGs in both emissions and concentration (Butt and McCarl, 2005, IPCC, 2007c). Reducing net carbon dioxide emissions to the atmosphere is increasingly being considered as a way of addressing the climate change problem. International efforts to stabilize the atmospheric concentration of GHGs resulted in a 1997 treaty, the Kyoto Protocol, which was developed with the involvement of over 160 countries, including the U.S. (Butt and McCarl, 2005). In the Kyoto Protocol, the developed countries (like the U.S., U.K. and Canada) agreed to limit their GHG emissions, rolling back to below the levels emitted in 1990. U.S. emissions are about six billion metric tons (tonnes) of carbon dioxide plus about 1 million more carbon dioxide-equivalent (CO2e) in other gasses. Within the Kyoto Protocol, the U.S. emissions were to be reduced to seven percent below 1990 levels by 2008-2012, which given projected emissions growth would have required scaling back emissions by 30 to 40 percent of what would have occurred in the 2008-2012 time period or 2.1 to 2.8 billion tonnes of CO2e.
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 | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.039 | 0.006 |
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".