Distribution of glyphosate and cloransulam-methyl resistant giant ragweed (<i>Ambrosia trifida</i> L.) populations in southern Ontario
Bibliographic record
Abstract
Giant ragweed is a very competitive weed in row crop production and has been found to drastically reduce soybean yield. In 2008, giant ragweed was the first weed species with confirmed resistance to glyphosate in Canada. As of 2010 there were 48 locations with confirmed glyphosate resistant giant ragweed in Essex, Kent and Lambton counties. In addition, there was suspected resistance to cloransulam-methyl. The objectives of this research were 1) to conduct an expanded field survey on the distribution of glyphosate resistant giant ragweed in Ontario, 2) to determine the distribution of cloransulam-methyl resistant giant ragweed in Ontario, and 3) to determine the distribution of multiple resistant (glyphosate and cloransulam-methyl) giant ragweed in Ontario. In 2011 and 2012 giant ragweed seed was collected from 85 field sites in Essex (16), Kent (34), Lambton (23), Elgin (3), Middlesex (6), Lennox & Addington (1), Huron (1) and Brant (1) counties. In total there are 34 additional locations confirmed with glyphosate resistant giant ragweed in Ontario. There are 11 locations confirmed with cloransulam-methyl resistant giant ragweed and 5 locations with multiple resistance to both glyphosate and cloransulam-methyl. Glyphosate resistant giant ragweed has been found in 4 additional counties.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".