Soil Carbon Sequestration in Mexico and Central America (Biome A)
Bibliographic record
Abstract
The current change in the global climate is attributed to the unprecedented concentration in the atmosphere of greenhouse gases (GHGs). The main GHGs are CO2, N2O, CH4, and CFCs. Agricultural activities, including land use and land-use change, constitute an important source of GHG, being responsible for 25 percent of CO2, 50 percent of CH4, and 70 percent of N2O emitted by all human activities (Agriculture and Agri-Food Canada, 1998). At a global level, agricultural activities use approximately 35 percent of all the existing lands on the planet. If the accumulation of GHGs continues at the present rate, experts predict an increase in the average global temperature between 3 and 5°C by the end of the twenty-first century (IPCC, 1996, 2001). Because such increase may have serious consequences for humankind, mitigation measures must be adopted by all nations of the world. One of this mitigation measures is to increase carbon (C) stock in the major components of the ecosystems. Plants and soil are two major compo- nents of the ecosystems with a high C sequestration potential which merit both basic and adaptive research.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".