Long-term trends of climate change and its impact on crop growing season on Montreal Island
Bibliographic record
Abstract
Long-term trends in air temperature and precipitation under climate change were analyzed for two meteorological stations on the Island of Montreal: McGill (1872–1986) and Pierre-Elliott-Trudeau (P-E-T, formerly Dorval) Airport (1942–2014). A linear trendline analysis, the Mann–Kendall (MK) test and the two-sample Kolmogorov–Smirnov (KS) test were conducted to assess specific climate trends. On a 100-year basis, temperature increased 1.88°C (34%) and 1.18°C (19%) at the McGill and P-E-T Airport sites, respectively, while annual rainfall increased 23.9 mm y−1 (2.3%) and 138.8 mm y−1 (15%) over the same period. The frequency of 50% (every other year) and 95% (every year) annual maximum daily rainfall events showed decreasing trends for the McGill station, but increasing trends for the P-E-T Airport station. Growing degree-days and growing season length are prone to being influenced by climate change and are critical to managing agricultural activities in the Montreal region; both showed increasing trends. At the same time, the onset of the growing season occurred earlier as time progressed.
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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 | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".