Paralysing January 1999 Snowstorms Produced Minimal Streamflow for Southern Ontario
Bibliographic record
Abstract
On January 2, 1999, the city of Toronto and surrounding regions of southern Ontario, Canada were brought to a standstill by a large storm event that resulted in near–record snowfalls. Several smaller winter storms followed and by January 15 approximately 100 cm of snow had fallen across the area, creating a flooding concern for water resources managers. A statistical analysis of the 1999 snowpack depth and snow water equivalent (SWE) for the Grand River Basin showed that the snow depths were the largest on record with two–week snow depth increases at several sites having return periods from 50 to 200 years. However, the amount of water in the snowpack was small, with the return period for SWE being between two and 21 years. Above freezing temperatures occurred in midJanuary partially melting the pack and producing some streamflow. No flooding occurred, and the spring peak streamflows were amongst the lowest on record.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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) | 0.004 | 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".