Experimental Study of Ice Jam Thickening under Dynamic Flow Conditions
Why this work is in the frame
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Bibliographic record
Abstract
River ice jams are a common occurrence on northern rivers, and their formation can present a severe flood risk to nearby communities. As more and more river regulation projects are developed to provide an alternative to fossil fuels for electrical power-generating capacity, our need to understand the mechanisms associated with ice jam formation under variable flow conditions becomes more vital. This is because, at present, hydropeaking operations are often severely curtailed during the ice-affected seasons due to concerns that sudden flow fluctuations might instigate ice jams and associated flooding. Here, an experimental investigation explores the effects of rapid increases in discharge on ice jam formation and evolution. It is found that the thickness of ice jams formed under highly dynamic flow conditions tend to be slightly thinner than those formed during steady carrier flows for comparable discharges. Also, despite the highly dynamic nature of these consolidation events, the resulting ice thicknesses appear reasonably well approximated by steady flow theory.
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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 | 0.000 |
| 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 it