Leaf Extension Rate May Help Determine When Low Wild Oat Herbicide Rates Will Be Effective<sup>1</sup>
Bibliographic record
Abstract
Determination of the active growth state of weeds may lead to more reliable predictions of herbicide efficacy. Experiments were conducted at Lacombe and Lethbridge, Alberta, Canada, from 1996 to 1998 to determine if wild oat leaf extension (growth) rate could be used to predict the efficacy of imazamethabenz and ICIA 0604. As expected, wild oat control increased and wild oat biomass decreased with increasing imazamethabenz and ICIA 0604 rates. Mean wild oat growth rates ranged from 6 to 44 mm over a 24-h time interval. Wild oat control at 25% of the recommended doses of ICIA 0604 or imazamethabenz increased as wild oat growth rate increased. However, wild oat growth rate did not influence herbicide efficacy at higher herbicide rates. Regression analysis confirmed that wild oat control at the lowest application rates increased 6 or 14% for every 10 mm of wild oat growth during the 24 h preceding herbicide application of ICIA 0604 or imazamethabenz, respectively. Covariance analysis confirmed the influence of wild oat growth rate on wild oat control by imazamethabenz but not by ICIA 0604. Monocot leaf extension rates may be useful for predicting herbicide efficacy in integrated weed management or decision support systems.Nomenclature: ICIA 0604, 2-[1-(ethoxyimino)propyl]-3-hydroxy-5-(2,4,6-trimethylphenyl)-cyclohex-2-enone (proposed common name: tralkoxydim); imazamethabenz; wild oat, Avena fatua L. #3 AVEFA.Additional index words: Active growth, integrated weed management, predicting efficacy, reduced rates.
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 | 0.001 |
| 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".