Characterization and Analysis of Gullies in the Sub-basin of Ribeirão Serra in Morrinhos, Goias, Brazil
Bibliographic record
Abstract
Due to the reduction of the vegetation cover, the exposed soil increases the erosive vulnerability, and reduces the organic matter content, factors that can aggravate with less production of vegetal mass and microbiological activity of the arable layers, rich in calcium carbonate and that increases the degradation of the soil structure leading to the formation of gullies. This study aimed to characterize and survey the physical, chemical and structural characteristics of soils of four gullies located in the sub-basin of Ribeirao Serra by means of physical-chemical parameters and subjected to multivariate analysis. Slope maps, hypsometry, drainage network and soil types were elaborated. Morphological description of the soil, georeferencing of the boundaries of each gullie, and collection of deformed soils samples for physical-chemical and structural analysis were performed. Soil samples were collected on the slopes of the gullies at three points of each erosion, with three replicates, one in each horizon (A, B and C) at depths ranging from 0 to 310 cm. Qualitative tests were also carried out to verify the presence of some substances in the soil, such as carbonates and manganese. The data were submitted to the multivariate analysis, by means of Discriminant Analysis of Partial Least Squares analysis to evaluate the grouping of gullies in relation to the analyzed elements (physical-chemical), identifying if the set of elements interact with each other and/or present similarities. There is a high degree of anthropization with the use of pasture cultivated around the four gullies studied. According to the multivariate analysis the gullies Barreiro, Vendinha and Capim, are different, while it resembles the gull of the Retreat with the gullies Vendinha and Capim. The chemical elements present greater weight than the physical ones, in the separation of the gullies through the multivariate model.
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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 | 0.000 | 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) | 0.000 | 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".