Pollen- and Seed-Mediated Gene Flow in Kochia (<i>Kochia scoparia</i>)
Bibliographic record
Abstract
Efficient natural dispersal of herbicide-resistance alleles via seed and pollen can markedly accelerate the incidence of herbicide-resistant weed populations across an agroecoregion. Studies were conducted in western Canada in 2014 and 2015 to investigate pollen- and seed-mediated gene flow in kochia. Pollen-mediated gene flow (PMGF) from glyphosate-resistant (GR) to non-GR kochia was quantified in a field trial (hub and spoke design) at Saskatoon, Saskatchewan. Seed-mediated gene flow of acetolactate synthase (ALS) inhibitor-resistant kochia as a function of tumbleweed speed and distance was estimated in cereal stubble fields at Lethbridge, Alberta and Scott, Saskatchewan. Regression analysis indicated that outcrossing from GR to adjacent non-GR kochia ranged from 5.3 to 7.5%, declining exponentially to 0.1 to 0.4% at 96 m distance. However, PMGF was significantly influenced by prevailing wind direction during pollination (maximum of 11 to 17% outcrossing down-wind). Seed dropped by tumbleweeds varied with distance and plant speed, approaching 90% or more (ca. 100,000 seeds or more) at distances of up to 1,000 m and plant speeds of up to 300 cm s–1. This study highlights the efficient proximal (pollen) and distal (seed) gene movement of this important GR weed.
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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 | 0.000 |
| 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 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".