A Study of Complex River Ice Processes in an Urban Reach of the North Saskatchewan River
Bibliographic record
Abstract
Northern rivers are affected by river ice processes for a significant portion of the year. This poses many challenges and opportunities to river ice engineers and geoscientists. Since 2009, several researchers have conducted a variety of river ice studies on the North Saskatchewan River through Edmonton, Alberta. This has resulted in a relatively comprehensive dataset which includes meteorological, hydrometric and river ice data. Analyses of these data have produced interesting results which are evidence of a highly complex ice regime. The conditions preceding and during freeze-up and break-up are highly variable. The University of Alberta’s River1D Ice Process model is used to investigate these phenomena by simulating the 2009-10 and 2010-11 winter seasons. The 29 km long study reach includes multiple bridging locations and the discharge from the Gold Bar Wastewater Treatment Plant (GBWTP). Simulation results are compared to the observed water surface elevation, ice front progression, surface pan concentration, border ice fraction, ice thickness, suspended frazil concentration, and water temperature data measured at several locations along the reach. Strong agreement between the observed and simulated data was achieved for an unprecedented number of river ice variables. The model can be sued as the foundation for future river ice studies in Edmonton and to help address specific problems or challenges that have been observed within the study reach.
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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 | 0.001 |
| 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".