Factors Affecting Weed Seed Devitalization with the Harrington Seed Destructor
Why this work is in the frame
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Bibliographic record
Abstract
The Harrington Seed Destructor (HSD), a novel weed control technology, has been highly effective in Australian cropping systems. To investigate its applicability to conditions in western Canada, stationary threshing was conducted to determine the impact of weed species, seed size, seed number, chaff load, and chaff type on efficacy of seed destruction. Control varied depending on species, with a range of 97.7% to 99.8%. Sieve-sized volunteer canola seed had a linear relationship of increasing control with increasing 1,000-seed weight. However, with greater than 98% control across all tested seed weights, it is unlikely that seed size alone will significantly influence control. Consistently high levels of control were observed at all tested seed densities (10 seeds to 1 million seeds). The response of weed seed control to chaff load was quadratic, but a narrow range of consistently high control (>97%) was again observed. Chaff type had a significant effect on weed seed control (98% to 98.6%); however, seed control values in canola chaff were likely confounded by a background presence of volunteer canola. Overall, the five parameters studied statistically influence control of weed seeds with the HSD. However, small differences between treatments are unlikely to affect the biological impact of the machine, which provides high levels of control for those weed seeds that can be introduced into the harvester.
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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 | 0.000 | 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 | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 it