Management of Soil Mulch in Weed Suppression and Sugarcane Productivity
Bibliographic record
Abstract
The soil mulch is an agricultural practice that can benefit soil fertility and can be effective in suppressing weeds. The objective this research was to evaluate the mulching from legumes in weed control and sugarcane (first harvest/cut) productivity, comparing the results with the conventional application of herbicides. This research was carried out under field conditions. Five legumes were managed in two ways to form the soil cover: (1) mechanical topple, and (2) chemically desiccated. To compare the results, used treatments with herbicides applied in pre and pre + post emergence. The soil mulch from mechanical topple of Crotalaria spectabilis, C. juncea, C. ochroleuca, C. breviflora and Cajanus cajan presented lower efficiency in suppressing weeds than the treatment with herbicides applied in pre + post-emergence, however, were more efficient in controlling weeds in relation to the use of herbicides in pre-emergence, a fact observed at 60 days of sugarcane cultivation.
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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".