Control Decision Rule for European Chafer (Coleoptera: Scarabaeidae) Larvae in Field Corn
Bibliographic record
Abstract
After greenhouse and outdoor microplot experiments, a critical density of two third instars per microplot for third instars of European chafer, Rhizotrogus (Amphimallon) majalis (Razoumowsky), in corn, Zea mays L., was derived. On average, the number of missing or damaged plants increased approximately 8% from zero to two larvae per 900 cm2. Furthermore, 23 fields in 2 yr were sampled for larvae along transects by using a golf cup cutter as the sampling tool and the critical density of 0.2 larva per sampling unit as the critical density. The sampling unit was one golf cup cutter with a diameter of 10.8 cm or 91.4 cm2 (10 sampling units approximately 900 cm2 approximately 1 foot2). Fieldwide means and variation were modeled to Taylor's power law, a = 1.42 and b = 1.47, and 20 of 23 fields fit the negative binomial probability distribution. Wald's formula for a sequential sampling plan was most accurate and least time-consuming, according to the operating characteristic and the average sample number function, relative to Iwao's and converging lines formulae. Percentage of sand, topography, soil bulk density, and proximity to trees were measured as potential predictors of areas with high larval density. Percentage of sand and soil bulk density were significant predictors, and topography and proximity to trees were not significant predictors. Field areas where the percentage of sand is high and the soil bulk density is low to moderate or where the percentage of sand is moderate and the soil bulk density is low should be chosen as sampling locations.
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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 | 0.001 | 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) | 0.001 | 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 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".