A study of drought characteristics over the Canadian prairies
Bibliographic record
Abstract
Droughts, a major concern to all of Canada, particularly to the Canadian Prairies, typically occur once every three years. Most research addressing such droughts has concentrated on the large‐scale conditions associated with this form of extreme weather whereas little research has been conducted on its smaller scale characteristics. The present study addresses these smaller scale issues. Several datasets (surface observations, drought indices, and precipitation data) were used to identify droughts occurring over the Prairies since 1953 and to compare their characteristics with those years associated with non‐drought conditions. Warm season, May to September, hourly surface observations (temperature, moisture, clouds, and precipitation type) from ten observation sites were compared for four categories of moisture across the Canadian Prairies, extreme drought, drought, non‐drought, and extreme wet conditions. When compared to non‐drought or extreme wet conditions, drought and extreme drought conditions are naturally associated with warmer temperatures and drier conditions; there is also little change in the amount of total cloud cover but cloud bases are higher and the maximum temperature occurs 1–2 h later in the afternoon. Near‐surface energy increases systematically from extreme wet to extreme drought conditions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".