Evaluating Seed Shatter of Economically Important Weed Species
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The increasing occurrence of herbicide resistance, along with no new herbicide modes of action developed in over 30 yr, have increased the need for nonherbicidal weed management strategies and tactics. Harvest weed seed control (HWSC) practices have been successfully adopted in Australia to manage problematic weeds. For HWSC to be effective, a high proportion of weed seeds must be retained on the plant at crop maturity. This 2-yr (2014, 2015) study evaluated seed shatter of wild oat, green foxtail, wild mustard, and cleavers in both an early (field pea) and late (spring wheat) maturity crop in field experiments at Scott, Saskatchewan. Seed shatter was assessed using shatter trays collected once a week during crop ripening stage, as well as at two crop maturation or harvest stages (swathing, direct-combining). Seed shatter differed among weed species, but was similar between crops at maturity: ca. 30% for wild oat, 5% for cleavers, < 2% for wild mustard, and < 1% for green foxtail. Overall, seed shatter of wild oat occurred sooner and at greater levels during the growing season compared with the other weed species. Viability of both shattered and plant-retained seeds was relatively high for all species. The small amount of seed shatter of cleavers, wild mustard, and green foxtail suggests that these species may be suitable candidates for HWSC. Due to the amount and timing of wild oat seed shatter, HWSC may not reduce population abundance of this grassy weed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 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 it