Sequential Sampling Plans for the Hairy Chinch Bug (Hemiptera: Lygaeidae)
Bibliographic record
Abstract
Two sequential sampling plans were developed to produce tools to reduce the use of pesticides for the control of the hairy chinch bug, Blissus leucopterus hirtus Montandon, on turfgrass lawns in the cool-humid region of Quebec, Canada. A first plan based on Wald's method was shown to be too conservative in a validation conducted on infested lawns. The second plan developed using Iwao's method yielded good results. The difference between the two plans may have occurred because no common k could be found for the negative binomial functions describing chinch bug distribution on lawns, thereby violating an essential assumption of Wald's approach. Application of the Iwao plan, which is based on visual sampling of 0.1-m2 quadrats, requires approximately 20 min when lawn evaluation is conducted by a single person. Estimation of the occurrence of chinch bug infestations (28% infested lawns in the regions of Montreal and Quebec cities), and results from validation of the Iwao plan on infested lawns, indicate that the error rates alpha and beta of the plan are lower than an upper limit of 0.05 and 0.14, respectively. The adequate precision and practicality of this plan suggest that it could become an essential tool for management of turfgrass lawns in regions where the hairy chinch bug completes less than two generations per growing season.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".