Weed community response to contrasting integrated weed management systems for cool dryland annual crops
Bibliographic record
Abstract
ThomasAG, LégèreA, LeesonJY, StevensonFC, HolmFA & GradinB (2011). Weed community response to contrasting integrated weed management systems for cool dryland annual crops.Weed Research 51, 41–50. Summary Contrasting approaches to integrated weed management (IWM) for prairie cropping systems were evaluated by measuring weed response to six IWM systems in a wheat–oilseed rape–barley–pea rotation at Saskatoon and Watrous, Saskatchewan, Canada. The six IWM systems (high herbicide/zero tillage; medium herbicide/zero tillage; low herbicide/zero tillage; low herbicide/low tillage; medium herbicide/medium tillage; no herbicide/high tillage) included various combinations of seeding rate and date, herbicide timing and rate, and tillage operations, in order to achieve similar weed management levels. Changes in weed communities were assessed over 4 years by monitoring species composition and abundance at various times during the growth season. Principal response curves indicated a gradual increase inThlaspi arvense,Chenopodium album,Amaranthus retroflexusandFallopia convolvulusin the no herbicide/high tillage system. Winter and early spring annuals and perennials increased in most systems, but particularly in the low herbicide/zero tillage and medium herbicide/zero tillage systems. Although five of the six IWM systems provided similar results, changes in weed communities would suggest that operations could be revised to improve the overall management of certain weed species and reduce seed return in the no herbicide/high tillage system and in systems with low herbicide inputs and zero tillage. This study confirms the potential of contrasting IWM systems under the challenging environmental conditions of the Canadian Prairies.
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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 | 0.000 | 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".