A Meta-analysis of Canada Thistle (<i>Cirsium arvense</i>) Management
Bibliographic record
Abstract
Abstract Although stand-alone and integrated management techniques have been cited as viable approaches to managing Canada thistle [Cirsium arvense(L.) Scop.], it continues to impact annual cropping and perennial systems worldwide. We conducted meta-analyses assessing effectiveness of management techniques and herbicide mechanism of action groups for controllingC. arvenseusing 55 studies conducted in annual cropping systems and 45 studies in perennial systems. Herbicide was the most studied technique in both types of systems and was effective at reducingC. arvense. However, integrated multitactic techniques, with or without herbicides, were more effective than sole reliance on herbicides for long-term control in both annual cropping and perennial systems. A variety of management techniques such as biocontrol, crop diversification, mowing, and soil disturbance provided control similar to that of herbicide. Our results suggest that many management techniques aimed at reducingC. arvensecan also improve crop yield or abundance of desired plants. This study highlights the need to devote more research to nonchemical and integrated management approaches forC. arvensecontrol.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.031 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".