Potassium Fertilization in Soybean and Its Correlation With Electrical Conductivity in Soil
Why this work is in the frame
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Bibliographic record
Abstract
Soybeans stand out among the main oilseeds in the world, with potassium (K+) as the second most required nutrient and exported by the plant. The objective of this study was to evaluate the effect of potassium fertilization on soybean crop and its correlation with the electrical conductivity in a Yellow Dystrophic Latosol in the Cerrado of Maranhão. The experiments were conducted in the years of 2015 and 2016. The design was a randomized block design, with five treatments and five replications. Treatments consisted of the following K2O doses: 0, 50, 100, 200 and 300 kg ha-1 in the sowing groove. The data collected were submitted to analysis of variance and regression. The response of soybean to potassium fertilization occurred for the mass of 100 grains. The highest grain yield was evidenced in the first year of soybean cultivation. The increase in the adjustment parameters of the regression models in the electrical conductivity of 20-40 cm in the second year of cultivation occurred as a function of the increase of the potassium fertilization.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it