The Relational Research and Experience of Water Transfer during Freezing Period
Bibliographic record
Abstract
The phenomenon that rivers freeze in high latitude and cold regions is universal. Ice dam, ice cover and ice jam, which are formed by stack, jammed and collective ice, can increase river resistance and water stage, resulting in flood, construction damage and navigation problems. In order to find out safe methods for water transfer during freezing period, studying the formation and development regularity of the river ice has been concerned on by many countries. Some researchers have made study on this subject, such as the generation and evolution of frazil ice, shore ice, bottom ice, ice cover and ice jam, the resistance of freeze-up river, flow capacity and variation of water stage. On the base of the river ice study, the former USSR, Canada, north Europe take some effective measures to transfer water safely on their water transfer projects, and these countries have accumulated a few valuable experience. Because of the complication in river ice study, the theory and project experience of this subject are not perfect, and need further research. This paper introduces the river ice study and project experience during freezing period mentioned above.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".