Temperature and Precipitation Trends in Southwestern Saskatchewan Tell a Complex Long-Term Climate Change Story
Why this work is in the frame
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Bibliographic record
Abstract
Historical climate trends in southwestern Saskatchewan, Canada were analyzed using parametric linear regression and non-parametric Mann-Kendall trend detection approaches over various timeframes between 1886 and 2010. We find substantial variability for this region in the significance and magnitude of any temporal trends for daily maximum, minimum, and mean temperatures on an annual basis - as well as during the winter, spring, summer, and autumn periods - that is dependent on the time period chosen. Similar results are obtained for precipitation data in the study area. The results demonstrate that temperature and precipitation trends in southwestern Saskatchewan tell a complex long-term climate change story, containing substantial temporal trend heterogeneity, thereby necessitating caution when interpreting long-term climatic data - particularly in the context of larger-scale regional or global observations and predictions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it