Leafhopper Taxa and Populations in Southern Idaho
Bibliographic record
Abstract
Plant pathogens, including viruses, phytoplasmas, and spiroplasmas, can be transmitted by leafhoppers, which can cause important yield-limiting diseases in vegetables, orchard crops, vineyards, and field crops. The species distribution and vector status of leafhopper taxa in southern Idaho is an understudied but critical component for developing sustainable management approaches. Thus, during the 2020 and 2021 growing seasons, 11,215 leafhoppers were collected on yellow sticky cards in sagebrush steppe areas and next to sugar beet and common bean fields in five counties in southern Idaho. Thirty-four genera were identified, with the primary genera being Euscelidius spp. (46% of leafhoppers; mostly E. variegatus), Amblysellus spp. (14%), Ceratagallia spp. (12%), Dikraneura spp. (8%), Empoasca spp. (5%), Macrosteles spp. (5%; includes M. quadrilineatus), Psammotettix spp. (4%; includes P. attenuens, P. dentatus, and P. lividellus), Hecalus spp. (2%), and Giprus spp. (1%). Nineteen of the 34 genera found were not previously reported in Idaho, and some of these leafhoppers are capable of vectoring pathogens. For example, preliminary evidence for an Amblysellus sample suggests that Spiroplasma kunkelii was present, which is the causal agent for corn stunt disease, which was not known to be present in Idaho. These results contribute substantively to the cataloging of leafhopper taxa present in southern Idaho and will aid in developing vector and disease management decisions. [Formula: see text] Copyright © 2025 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".