Les insectes ravageurs importants de la pomme de terre au Canada
Bibliographic record
Abstract
The potato crop is estimated to contribute 63% to the vegetable revenue in Canada. Like most agricultural crops, the potato crop yield is compromised by attacks of several insect pests during the growing season. Pests such as the Colorado potato beetle, the European corn borer, wireworms and tuber flea beetle can cause serious problems for potato production. Lack of control applications can result in major economic losses to the producer. In Canada, growers employ an Integrated Pest Management approach by using several techniques to manage and keep pest populations below economic thresholds in the potato crop. Some of the techniques used are: monitoring populations with pheromone and bait traps, use of degree days to estimate emergence, scouting fields to determine population levels, use of economic thresholds for a more precise application of insecticides and biological, cultural and mechanical control techniques. The objective of several research projects in Canada is to develop and refine control techniques and obtain a better understanding of the pests. The main objective for both the growers and the researchers is to reduce the amount of pesticides needed to control these insect pests in potatoes, while maintaining economic benefits for the producers.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".