EVIDENCE OF CONTAMINATION OF PEDIGREED CANOLA (<i>BRASSICA NAPUS</i>) SEEDLOTS IN WESTERN CANADA WITH GENETICALLY ENGINEERED HERBICIDE RESISTANCE TRAITS
Bibliographic record
Abstract
The objective of this study was to survey pedigreed canola (Brassica napus L.) seedlots for contaminating herbicide resistance traits because of complaints from farmers regarding glyphosate [N‐(phosphonomethyl)glycine]‐resistant canola volunteers occurring unexpectedly in their fields at densities and in patterns that suggested that pollen‐mediated gene flow from neighboring fields in previous years was not the source of contamination. Twenty‐seven unique, commercial certified canola seedlot samples were collected. Glyphosate‐resistant seedlot samples were not collected. Canola samples were planted in the field, and when the canola had two to four true leaves, glyphosate, glufosinate [2‐amino‐4‐(hydroxymethylphosphinyl)butanoic acid], and thifensulfuron {methyl 3‐[[[[(4‐methoxy‐6‐methyl‐1,3,5‐triazin‐2‐yl)amino]carbonyl]amino]sulfonyl]‐2‐thiophenecarboxylate} herbicides were applied. Surviving canola plants were counted. Of the 27 seedlots, 14 had contamination levels above 0.25% and therefore failed the 99.75% cultivar purity guideline for certified canola seed. Three seedlots had glyphosate resistance contamination levels in excess of 2.0%. Unexpected contamination (even at 0.25%) can cause problems for producers that practice direct seeding and depend on glyphosate for nonselective, broad‐spectrum weed control. To avoid unexpected problems and costs, it is important that farmers are cognizant of the high probability that pedigreed canola seedlots are cross‐contaminated with the various herbicide resistance traits.
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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 | 0.001 |
| 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".