No-Tillage and Phosphate Fertilization Management on Soybean Culture in Brazilian Cerrado
Bibliographic record
Abstract
Despite the benefits of no-till practices, soil compaction is a problem that can cause, among other things, mechanical impediment to root growth and less response to soil fertilization. The objective of this study was to evaluate the effect of subsoiling and doses of phosphate fertilization on soybean that have been cultivated over ten years under no-till systems in the Brazilian Cerrado. The experiment consisted of a randomized complete block design in a 2 × 4 factorial arrangement. Two managements in consolidated no-tillage area were considered: with and without subsoiling, along with four levels of phosphate fertilization: 0, 100, 300 and 400 kg ha-1 of P2O5. The practice of subsoiling in an area with ten years of no-till system provided an increase of 124.38 kg ha-1 in soybean productivity. Soybean plants grown under no-tillage system, with subsoil management, showed better development and pod production. The maximum phosphorus efficiency, with subsoiling, was achieved with the dose of 172 kg ha-1 of P2O5, yielding 5,693.4 kg ha-1. In the no-tillage system, the maximum efficiency dose and crop yield were 159 kg ha-1 of P2O5 and 5434.2 kg ha-1, respectively.
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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 | 0.000 | 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 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".