Phytosociology of Weeds in Function of the Cultivation of Genetic Materials of Beans and Castor Hybrids under Intercrop and Monoculture in the Brazilian Midwest
Bibliographic record
Abstract
Despite the socioeconomic importance of beans and small-door castor hybrids, few studies have been carried out to investigate the phytosociological composition of weeds that interfere in this integrated production system. The objective of this work was to investigate the phytosociological composition of weeds in intercropped bean and castor hybrids adapted to mechanized harvesting, as well as in monoculture, involving genetic materials with different plant architectures. The design was randomized blocks, with four replications, and the treatments consisted of three bean cultivars with different growth habits and types (BRS Realce; BRS Esteio; Pérola), cultivated in an intercropped system with two small castor hybrids (Agima and Tamar), and the respective monoculture systems of the bean and castor hýbrids. Weed evaluation was performed 25 days after crop emergence. The bean growth habits and the size of castor hybrids directly affect the weed community, in both systems. Cenchrus echinatus and Alternanthera tenella species showed predominance in intercropping and monoculture conditions. The common bean monoculture and castor hybrids system, in general, provide greater problems with weeds compared to their respective monocultures, especially the Poaceae family. The weed species similarity indexes were higher than 75%.
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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 | 0.001 | 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".