Sampling plan for the coffee leaf miner <i>Leucoptera coffeella</i> with sex pheromone traps
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The population density of the coffee leaf miner Leucoptera coffeella (Guérin‐Méneville & Perrottet) (Lep., Lyonetiidae) can be estimated using pheromone traps in coffee fields as male capture reflects this pest damage based on previous correlational study. However, the spatial distribution of pheromone traps and their density are necessary to optimize the sampling procedure with pheromone traps. Therefore, the objectives of the present study were to determine the pheromone trap density required per hectare to sample coffee leaf miner populations and to determine the spatial distribution of the males of this pest species. The males were sampled every 8 days in 12 consecutive evaluations. Taylor’s power law and frequency distributions were used to recognize the distribution of the male capture data, which followed a negative binomial distribution. A common K was obtained, allowing the establishment of a single conventional sampling plan for the 12 fields investigated. The adjusted sampling plan requires eight traps in an area of 30 ha for a 25% precision error. Kriging‐generated maps allowed the simulation of male captures for 8, 12 and 20 traps per 30 ha and the results were compared with those obtained with absolute sampling resulting in R 2 ‐values of 0.30, 0.57 and 0.60 respectively. The traps were able to identify the more highly infested areas within the field and are a precise and efficient tool for sampling populations of L. coffeella.
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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 | 0.000 | 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 it