Distribution and abundance of an allergenic weed, common ragweed (<i>Ambrosia artemisiifolia</i> L.), in rural settings of southern Quebec, Canada
Bibliographic record
Abstract
Common ragweed (Ambrosia artemisiifolia L.) is an important weed of urban and rural settings in eastern Canada. Where the species is abundant, its wind-dispersed pollen is responsible for most cases of allergic rhinitis or “hayfever” in August and September. Despite its adverse health effects, there is little information on the actual abundance or distribution of ragweed plants in rural settings. Ragweed surveys were therefore done in July and August (after herbicide application) in corn and soybean fields, field borders and along rural roadsides surrounding two cities in southern Quebec. Based on zero-inflated Poisson regression models, ragweed density averaged 4.1 plants m -2 (Saint-Jean-sur-Richelieu area) and 16.1 plants m -2 (Salaberry-de-Valleyfield area) along roadsides. Ragweed density in field borders (1.3 plants m -2 ) and fields was lower than on roadsides. Conventionally tilled fields and fields where tillage was reduced had equivalent densities of ragweed. Ragweed abundance in fields was likely related to the efficacy of herbicides used in transgenic vs. conventional crops. Transgenic herbicide-resistant corn fields had higher ragweed densities than conventional fields (0.44 vs. 0.07 plants m -2 ), while herbicide-resistant soybean fields had lower densities than conventional fields (0.02 vs. 1.33 plants m -2 ). Field borders located closer to roadsides had slightly higher ragweed counts, while roadside densities did not depend on the proximity of a field entrance. This suggests that roadsides are currently potential sources of spread into fields more than the opposite. Further research on the pollen production and dispersal of these rural populations is needed.Key words: Weed density, corn, Zea mays, soybean, Glycine max, field border, field entrance, roadside, transgenic crops
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".