Hexazinone Resistance in Red Sorrel (<i>Rumex acetosella</i>)
Bibliographic record
Abstract
Biannual applications of hexazinone have been applied in many lowbush blueberry fields in Nova Scotia for more than 30 years. Persistent reliance on a single herbicide chemistry may have selected for hexazinone-resistant red sorrel. The recommended rate of hexazinone (1.92 kg ai ha−1) no longer controls red sorrel in many growing regions. Six levels of hexazinone (0, 0.48, 0.96, 1.92, 3.84, and 7.68 kg ai ha−1) were applied to red sorrel plants grown in a greenhouse from seeds collected from three commercial fields and a no blueberry area to determine if they were hexazinone resistant. Red sorrel from two sites where hexazinone had not been applied regularly died at the 0.96 kg ai ha−1rate of hexazinone whereas red sorrel from two commercial fields survived at 7.68 kg ai ha−1. It is concluded that red sorrel is hexazinone-resistant in some wild blueberry fields. A portion of thepsbA gene was sequenced and it was determined that resistant plants had a Phe to Val substitution at position 255 in the D1 protein. This is the first recorded instance of hexazinone resistance in a perennial broadleaf weed in blueberry fields.
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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 | 0.000 | 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) | 0.001 | 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".