Structural Alterations of Paraná’s Oxisols by Cover Crops
Bibliographic record
Abstract
This work aimed to evaluate the dynamics of physical and hydric attributes of a clayey Latosol cultivated with different cover species. The experimental area was located in the Agronomic Institute of Paraná (IAPAR), in the regional hub of Santa Tereza do Oeste, Paraná, Brazil. The experiment was comprised of seven cover species also called treatments is the course of this work. Three of them were isolated summer species notably Crotalaria juncea, Crotalaria spectabilis, Cajanus cajan (pigeon pea), and the other four treatments winter species cultivated individually or in association including Avena strigosa (Black oat), + (Avena stirgosa + Raphamus sativus (radish), Avena strigosa + Lupinus albus (Lupin bean), and (Avena strigosa + Pisum sativum (pea). The treatments were distributed on a completely random plots of 20 m × 25 m without replication. Soil density, macroporosity, and saturated hydraulic conductivity were measured to follow the changes of the soil structure. Statistical analyses showed that cover crops species did not lead to a significant improvement in soil structural status. Soil density varied between 1.08 and 1.12 Mg m-3, macroporosity from 15.22 and 16.90%, and saturated hydraulic conductivity ranged from 28.83 to 45.07 mm h-1. Soybean grain yield were considered satisfactory in 2016 (mean = 1909.68 kg ha-1) and in 2017 (mean = 3355.30 kg ha-1) most probably due to the good initial structural conditions of the soil, alongside with the good climatic conditions during the two campaigns. Furthermore, the soybean grain yield was positively influenced by Ds which ranged from 1.0 to 1.17 Mg m-3.
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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".