Distribution of Pests on Vitis riparia in Sandy Soils of the South-Western Ontario
Bibliographic record
Abstract
Vitis riparia (Michaux) is native to North America and tolerates the local weather and soil conditions of south-western Ontario in Canada. A survey was done on V. riparia to elicit the distribution of pests on the species in central south-western Ontario. Eight hundred and forty four genotypes of V. riparia were observed throughout the sandy soils of five counties in Ontario (Brant, Elgin, Middlesex, Norfolk and Oxford). The location of the selected vines was labeled in the Geographic Information System (GIS). The ArcGIS program was used to make maps of the distribution of the wild grape pests, Phylloxera, Japanese beetle, Filbert gallmaker, Cane Filbert gallmaker, Tumid Filbert gallmaker and Tube Filbert gallmaker midges in those areas. The results show that the density of pests on V. riparia is more severe in some areas than others. Phylloxera and Japanese beetle were the major pests observed. Phylloxera was most prevalent and Japanese beetle least prevalent in Elgin County. The gallmaker midges were found in low densities throughout the area. The distribution of Phylloxera could be related to the soil type, and the distribution of Japanese beetle and Tumid gall midge to the land use. With Phylloxera, it appears that they prefer poor drainage soils which do not dry out readily. Whereas, Japanese beetle and Tumid gall midge prefer undisturbed soils where they can overwinter successfully.
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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 | 0.000 |
| 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".