Remote monitoring of stored grain insect pests
Bibliographic record
Abstract
A number of remote sensing methods were developed and tested in commercial grain warehouses; probe pitfall traps attached to vacuum lines, surface pit fall traps equipped with video cameras and white boards on grain surface monitored with video cameras. These methods were compared with detecting insects using grain samples. Warehouse trials by trapped methods were carried out in bins with 8520 t of wheat from 23 May until 8 August 2016.Grain temperatures were from 22.7 to 31.6?. Psocids,Liposcelis bostrychophila Badonnel,were detected by grain samples, but there were higher number of pscoids trapped with the probe pitfall traps and pitfall traps than found in grain samples. Plodia interpunctella (Hübener), Sitophlius zeamais Motchulsky and Cryptolestes ferrugineus (Stephens) were detected by probe pitfall trap, but not in the grain samples. S. zeamais was detected by the pit fall traps. Using the remote controlled video camera in the warehouse head space, we were able to distinguish and count S. zeamais, C. ferrugineus and psocids on white boards. The video from pitfall traps can be sent to mobile phones. With all these methods, data can be collected remotely, and could be analyzed by imagine analysis allowing for rapid real time monitoring of insect pests.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".