Physical attributes of soil under amazon forest conversion for different crop systems in southern Amazonas, Brazil
Bibliographic record
Abstract
The conversion of forested areas into cropping systems modifies the soil physical attributes and affects the environmental and economic sustainability of agricultural activity. Thus, this work aimed to evaluate the modifications caused in the physical attributes of the soil in the area of guarana, cupuacu, and annatto compared with forest area in southern Amazonas. In the areas of forest and guarana meshes of 90 m × 70 m and regular spacing between the sampling points of 10 m × 10 m, in the area of annatto meshes of 90 m × 56 m and spacing of 10 m × 8 m, for cupuacu meshes of 54 m × 42 m, with spacing between the sampling points of 6 m × 6 m. The samples were collected in the depths of 0.00–0.05, 0.05–0.10, and 0.10–0.20 m, with 80 sampling points in each area, making 960 samples in the four areas. The cupuacu area most closely resembled the most diverse aspects of soil physical attributes with the forest area, and this was noticeable through the averaging test along with the principal component analysis, thus indicating that this crop is the least harmful to the studied soil, as well as the adopted systems of cultivation cause modifications mostly superficially, being these modifications little noticeable in layers superior to 10 cm.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".