Evaluation of Tag Entanglement as a Factor in Harmonic Radar Studies of Insect Dispersal
Bibliographic record
Abstract
The observation of insects and other small organisms entangled in the habitat after the addition of vertical or trailing electronic tags to their body has generated concerns on the suitability of harmonic radars to track the dispersal of insects. This study compared the walking behavior of adult Colorado potato beetle (Leptinotarsa decemlineata (Say) Chrysomelidae), plum curculio (Conotrachelus nenuphar (Herbst) Curculionidae), and western corn rootworm (Diabrotica virgifera virgifera (LeConte) Chrysomelidae) with and without vertical and or trailing tags in field plots or arenas. The frequency of the larger Colorado potato beetles crossing bare ground or grassy plots was unaffected by the presence of an 8 cm trailing harmonic radar tag. However, plum curculios and western corn rootworms, were either unable to walk with a 4 cm trailing tag (plum curculio) or displayed a reduced ability to successfully cross a bare ground arena. Our results revealed the significant impact of vegetation on successful insect dispersal, whether tagged or not. The vertical movement of these insects on stems, stalks, and tubes was also unaffected by the presence of vertical tags. Trailing tags had a significant negative effect on the vertical movement of the western corn rootworm. Results show that harmonic radar technology is a suitable method for studying the walking paths of the three insects with appropriate tag type and size. The nuisance factor generated by appropriately sized tags was small relative to that of vegetation.
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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".