Geostatistics and Sample Density of Chemical Attributes for Soil under Sugarcane and Agroforestry in Humaitá – AM, Brazil
Bibliographic record
Abstract
There is a lack of studies focusing on spatial variance of chemical attributes in Amazonas, Brazil. The objective of this study was to evaluate geo-statistics and sample density of chemical attributes in soils under sugarcane and agroforestry, Humaitá, Amazon state, Brazil. The research was carried out in the municipality of Humaitá, Amazon state, the areas were in meshes of 70 m x 70 m regularly spaced by 10 m, with 64 points per area, and then soil samples were collected in layers of 0.0-0.2 m and 0.4-0.6 m. We performed chemical analyses of the proprieties of soil. Then, it was applied descriptive statistics, geo-statistics and sample density techniques based on semivariogram coefficient of variation and range. As a result, we observed spatial dependence for most of the chemical proprieties in the two areas. Based on Cline, sugarcane presented a sample density of 237 (0.0-0.2 m) and 225 (0.4-0.6 m); and agroforestry had 356 (0.0-0.2 m) and 465 (0.4-0.6 m) points per hectare. Yet in the range sample density, sugarcane showed 30 (0.0-0.2 m) and 5 (0.4-0.6 m), whereas agroforestry areas had 23 (0.0-0.2 m) and 9 (0.4-0.6 m) points per ha.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 teacher head, 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".