Local and regional approaches to studying the phenology and biological control of the soybean aphid
Bibliographic record
Abstract
Soybean aphids Aphis glycines Matsumura (Hemiptera: Aphididae) are an economic pest of soybean Glycine max (L.) Merr. in much of the United States and parts of Canada. Some crucial phenological information of A. glycines is unknown, specifically source-sink dynamics between and within host plants and factors guiding aphid migrations. In addition, there are discrepancies in the literature on the importance of food webs and how local landscape effects can alter A. glycines populations. Increasing our understanding of A. glycines population dynamics may improve predictions of aphid outbreaks and integrated pest management efforts. The first objective was to determine how landscape composition and heterogeneity impact A. glycines and their natural predator community. This study was centered in and around the Neal Smith National Wildlife Refuge located in Jasper County, Iowa. A second objective was to determine how prairie plantings adjacent to soybean impact A. glycines and natural enemy populations. To accomplish this, four study sites in central Iowa, transects were established up to 200 m in both soybean and prairie. A third objective was to describe A. glycines movement patterns on a regional scale. We monitored winged aphids (alates) using a suction trap network established at 42 locations over 10 states. Alates where correlated with northern latitudes which led to the last objective which was to predict A. glycines using low temperature data from the Midwest US and determine whether temperatures have reached A. glycines supercooling point (-34oC).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".