Impact of root fragment dimension, weight, burial depth, and water regime on Cirsium arvense emergence and growth
Bibliographic record
Abstract
Sciegienka, J. K., Keren, E. N. and Menalled, F. D. 2011. Impact of root fragment dimension, weight, burial depth, and water regime on Cirsium arvense emergence and growth. Can. J. Plant Sci. 91: 1027–1036. Cirsium arvense is an aggressive, introduced, perennial invasive weed that flourishes in a wide variety of environments including conventional and organic agricultural systems as well as disturbed non-crop habitats. Even though much research has been conducted on the chemical, biological, and cultural management of C. arvense, less information is available on how pre-emergence factors affect its reproductive biology and growth. This research assessed the combined impact of root fragment size, root fragment biomass, burial depth, and water regime (a proxy of water availability) on C. arvenseemergence and growth in fallow conditions. In field experiments, root burial depth was the most important factor determining C. arvenseemergence and growth, with roots at the 10-cm depth having the greatest average emergence (51.2±2.0% in 2007 and 43.5±7.2% in 2008; mean±SEM) compared to roots at the 2 cm (8.9±7.4% in 2007 and 38.1±8.3% in 2008) or 20 cm (12.8±4.0% in 2007 and 17.6±2.7% in 2008) depth. In greenhouse experiments, water regime was the overriding variable determining C. arvense emergence as well as above-ground and below-ground biomass. These results could improve decision-aid models and enhance the efficacy of site-specific C. arvense management practices.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".