Predispersal weed seed predation in soybean fields
Bibliographic record
Abstract
The role of predispersal weed seed predation on the population dynamics of weeds is largely unknown in an agricultural setting. The hypothesis for this study is that enhanced levels of predispersal weed seed predation by natural seed predators are a result of disturbance (no-till) in combination with altered microclimate (planting strategy). A two-year study was designed to test this hypothesis in 1998 and 1999 at the Woodstock research station, Ontario. Soybeans were grown in narrow (19 cm) and wide (76 cm) rows in both no-till and tilled soils. Levels of seed predation were measured using seeds of redroot pigweed ('Amaranthus retroflexus' L., Amaranthaceae) and common lambsquarters ('Chenopodium album' L., Chenopodiaceae). The larvae of 'Coleophora lineapuvella' Chambers (Lepidoptera: Coleophoridae), were identified as being responsible for seed damage primarily within 'A. retroflexus'. Results show that seed predation of ' A. retroflexus' ranged from <1 to 17% and that the soybean treatment with the highest level of predispersal seed predation was in wide row no-till plantings. An interaction was found between tillage and row width for ' A. retroflexus' but not 'C. album'. Crop management strategies that enhance predispersal seed predation may prove to be an important weed management tool and may add another dimension to integrated weed management.
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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".