AGROECOLOGÍA Y BIODIVERSIDAD DE LAS SABANAS EN LOS LLANOS ORIENTALES DE COLOMBIA
Bibliographic record
Abstract
The Neotropical savanna ecosystem encompasses the plains of Colombia and Venezuela, the Brazilian Cerrados, and the savannas of Bolivia and Guyana. The 250 million hectares involved have been subjected to human intervention since the 1970s, including the introduction of improved grasses, development of 50% of the Brazilian cattle herd, and extension of soybean cultivation. The expansion of the agricultural and livestock frontier brings with it the development of road infrastructure and petroleum exploitation. The impact on the ecosystem deserves attention. For example, the Orinoquian Plains belong to the basin and delta of South America's third largest river by volume (the Orinoco) and the sixth by contribution of sediments. The development of this basin (900,000 km2) would have, without doubt, a scarcely imagined, effect of international dimensions. The intensification of production systems will affect native vegetation whose conservation implies integration with introduced species, especially forages. This collaborative work provides, over 12 chapters, an inventory of native species and their characterization, a description of experiments that measured the effects of fire and grazing in the savannas, a study of soil macrofauna, and recommendations for the intensive and rational use of native savanna. One of several appendices contains two illustrated synoptic keys (original and unique) identifying grass species in a representative section of higher lying savannas known as altillanuras.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 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".