Atmospheric and Oceanic Variability Associated with Growing Season Droughts and Pluvials on the Canadian Prairies
Bibliographic record
Abstract
This study documents and assesses the atmospheric and oceanic variability associated with growing season (May to August) droughts on the Canadian Prairies. For comparison, extreme wet seasons or pluvials are also examined. Using the Palmer Z-Index as a drought indicator, extreme dry and wet seasons are first identified for the period 1950 to 2007. Interrelationships among several atmospheric parameters including large- to synoptic-scale circulation patterns, low-level moisture transport, moisture convergence, precipitable water content and cyclone frequency are then assessed during extreme drought and pluvial periods. In addition, links to the previous winter's global sea surface temperature (SST) patterns are identified using the multivariate technique of singular value decomposition. Results show that moisture from the Gulf of Mexico is notably decreased during the identified drought seasons. Stronger than normal subsidence associated with anomalously high pressure over northwestern North America also l...
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".