Resistance of river ice covers to mobilization and implications for breakup progression in Peace River, Canada
Bibliographic record
Abstract
Abstract Prediction and modelling of ice breakup initiation and progress over extended river reaches is largely unattainable at present, despite the ecological and socio‐economic significance of the breakup event and associated ice jams that form in many rivers of Asia, Europe and North America. A key question is how to quantify the driving and resisting forces that are applied on the winter ice cover, which control the timing of its dislodgment, mobilization and subsequent jamming locations. Using a physics‐based onset criterion, explicit expressions for these forces are formulated. The more complex of the two is the resistance, which comprises components related to ice strength and thickness, channel curvature, thermal degradation of the ice cover during the pre‐breakup period, and freezeup level (defined as peak 7‐day running average water level during late fall and early winter). This insight is then used in a case study of recent dynamic breakups in a major Canadian river, explaining apparently random differences in the rate of advance of the breakup front among three different years. It is shown further that contradictory results are obtained when the effect of the freezeup level is ignored.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".