Smother Crop Mixtures for Canada Thistle (<i>Cirsium arvense</i>) Suppression in Organic Transition
Bibliographic record
Abstract
Canada thistle poses a particular threat to organic producers in temperate agriculture due to its ability to reproduce through an extensive system of underground roots. The Canada thistle life cycle, growth, and development are seasonally affected, and exploiting this biology may be useful for weed management. The objective of this study was to evaluate smother crop mixtures, seeded at different times, for Canada thistle control. Field trials were established in 2009 and 2010 to evaluate the ability of smother crop mixtures to suppress Canada thistle growth and development. Canada thistle aboveground biomass was suppressed 50% in 2009 and 87% in 2010 by the sorghum–sudangrass mixture, averaged over planting times. The oat mixture suppressed annual weed biomass more than 58% in 2009 and 67% in 2010 in all planting dates. Percent cover of Canada thistle was affected by crop mixture in 2009 and 2010, with sorghum–sudangrass being the most suppressive. The sorghum–sudangrass mixture was more suppressive of Canada thistle, probably because it included soybean and sunflower, all high-biomass, competitive crops. Planting date affected smother crop suppression of Canada thistle growth, but the effect was not consistent between 2009 and 2010 due to differences in weather conditions.
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.
How this classification was reachedexpand
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 | 0.000 | 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 teacher head, 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".