<i></i>LINURON RESISTANT COMMON RAGWEED (<i>AMBROSIA ARTEMISIIFOLIA</i>) POPULATIONS IN QUEBEC CARROT FIELDS: PRESENCE AND DISTRIBUTION OF TARGET SITE AND NON-TARGET SITE RESISTANT BIOTYPES
Bibliographic record
Abstract
Common ragweed (Ambrosia artemisiifolia L.) is frequently observed in Québec carrot fields. Carrot growers essentially rely on linuron, a photosystem II inhibitor, to control this broadleaf weed. A linuron-resistant biotype had been identified but its prevalence was unknown and the genetic basis of resistance was not established. Consequently, a survey was conducted and plants suspected to be resistant were collected in 2012 and 2013. Progeny from these plants were sprayed with a diagnostic rate of linuron and tested for the presence of target site mutations in the psbA gene. Common ragweed was the most reported species (95% of accounts) and 94% of populations were diagnosed as resistant. A new target site mutation was found in 37.5% of resistant populations tested. No mutations in the psbA gene known to confer resistance to linuron were found in the other resistant populations. Except for two populations, target site resistant plants were located in the muck soil production area, while those diagnosed as non-target site resistant were found in sandy fields located in a different area. To our knowledge, this is the first report of a Val219Ile mutation in the psbA gene of common ragweed and of evolved non-target site resistance to linuron.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".