Physical and Chemical Attributes of Yellow Oxisol With the Application of Cassava Wastewater After Intensive Mechanical Preparation
Bibliographic record
Abstract
The objective of this work was to evaluate the effect of the application of cassava wastewater in the production of dry mass of the spontaneous vegetation and in the physical and chemical attributes of a Dystrocohesive Yellow Oxisol submitted to intensive mechanical preparation in the Bahia Recôncavo. The experimental design was a 2 × 2 factorial scheme in 4 randomized blocks, the bands consisting of the intensity of the mechanical preparation of plowing followed by sorting: T0: without preparation; T1: 4 preparations; T2: 8 preparations and T3: 12 preparations; the first factor is the presence of cassava wastewater: M-with cassava wastewater; W-only water and the second factor presence or not of vegetation: CV-with vegetation and SV-without vegetation. The results of the analysis of soil attributes in the depth of 0.0-0.15 m showed that the pH, saturation by base (V%), macroporosity (Ma) and total porosity (TP) decreased linearly with the increase of the intensity of the mechanical preparation, however soil density (SD) increased. The application of cassava wastewater reduced the resistance to penetration (PR), pH and Ca2+ and V% of the soil and increased the dry mass productivity of the spontaneous vegetation and the contents of phosphor.
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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) | 0.001 | 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".