Les effets du climat sur les populations d’insectes ravageurs
Bibliographic record
Abstract
The impact of climate on insect pest populationsA changing climate will create new environments for insect pests in Canada and around the world.Longer, warmer summers and milder winters could result in greater overwinter survival of pests, a northward expansion, and invasion of new insect pests.While farmers and agronomists can manage pest insects using a variety of chemical, cultural (manipulation of a farming practice like planting date, seeding rates, tillage), and biological control tactics, understanding how they respond to weather and climate (in the short and long term) is critical to making informed pest management decisions.That is why Agriculture and Agri-Food Canada (AAFC) scientists in western Canada are studying the biology and population of insect pests, including how they respond to changing climatic conditions.To do this, entomologists conduct field and laboratory research, contribute to annual pest monitoring, and use historical data to develop models that help them better understand how climate affects insect pest populations and how these changes affect crop yields.In addition, the Prairie Pest Monitoring Network (PPMN), entomologists and volunteers who research and monitor insect pests, have supported crop protection programs on the prairies since 1997 and developed vast datasets on insect pest distribution and abundance.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".