Predicting crop damage caused by wireworms and the effect of tillage on trap efficiency
Bibliographic record
Abstract
Abstract A novel wireworm ‘probe’ trap is described, characterized, and used in field trials to (i) determine effects of different spring tillage treatments on its efficiency capturing Agriotes obscurus L. Coleoptera: Elateridae wireworms; and (ii) assess its ability to predict crop damage. In pot trials, its attractiveness to other wireworm species was determined. In a forage/grass field, spring tillage treatments included: ploughing, rototilling, glyphosate-sprayed then ploughing, glyphosate-sprayed then rototilling, glyphosate-sprayed untilled, and untilled. The number of wireworms captured in tilled treatments increased until 20 October. The number of wireworms captured in untilled treatments remained low. Subterranean CO2 levels in tilled treatments decreased after tillage and over the trapping period, suggesting the increase in captured wireworms occurred because trap CO2 levels were not overwhelmed by soil levels. The decrease in subterranean CO2 was less pronounced in untilled-glyphosate and relatively unchanged in untilled-no glyphosate, corresponding to the lower number of wireworms captured. In a separate trial determining the trap’s ability to predict crop damage, a 2 m-wide section was rototilled in grass/forage fields in the spring of Year 1. Probe traps assessed wireworm levels in August and October of Year 1 to predict crop damage for potato and corn planted in Year 2. The y-intercept of linear equations suggested that wireworms captured in October better-predicted potato damage and corn emergence although equations were significant only for August. October-captured wireworms ≤ 21 mm in length correlated better with crop damage than larger wireworms. Pot studies revealed the probe trap to also attract A. litigiousus, A. sordidus, A. brevis, and A. ustulatus.
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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 | 0.001 | 0.002 |
| 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 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".