The entomology of vineyards in Canada
Bibliographic record
Abstract
Abstract In Canada, viticulture has been practiced since the arrival of European settlers. After a period of low activity due to the prohibition in North America, viticulture enjoyed a renaissance in the 1970s such that it became a rapidly growing industry in Canada. It is currently practiced mainly in five provinces, i.e. , British Columbia, Ontario, Québec, Nova Scotia, and New Brunswick. In Eastern Canada, several species of wild vines ( Vitis Linnaeus; Vitaceae) grew naturally before cultivation of domesticated cultivars and these had their entomofauna. In contrast, no wild vines grew in British Columbia. As a consequence, the insect fauna varies according to the provinces and the regions and the agroclimatic conditions. Here we review the literature relevant to viticultural entomology in Canada and discuss the main grape insects. It is noteworthy that certain insect pests of grapes were the subject of the first issues of The Canadian Entomologist . Selected milestones are provided to document the evolution of research in grape entomology in the context of dynamic evolving viticultural and oenological industries. In recent years, the arrival of several invasive species challenged the sustainability of integrated pest management programmes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".