Weed community response to contrasting integrated weed management systems for cool dryland annual crops
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
T homas AG, L égère A, L eeson JY, S tevenson FC, H olm FA & G radin B (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 in Thlaspi arvense , Chenopodium album , Amaranthus retroflexus and Fallopia convolvulus in 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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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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