Lessons learned from past ice-jam floods concerning the challenges of flood mapping
Bibliographic record
Abstract
Delineation of flood hazard and risk on maps is useful as a means of public education and as a basis for measures aimed at lessening future flood damages. In many northern countries, rivers and streams are prone to ice-related flooding that often results in higher water levels and more extensive damages than open-water events. Procedures and standards for analysing ice-related flooding, however, are much less common than well-established standardized approaches for the open-water events. Nonetheless, the inherent flood hazard along many northern and mid-latitude rivers is not fully represented on flood-plain, flood-hazard, and flood-risk mapping if the possibility of ice-jam floods is ignored. Fortunately, the biophysical, past-flood, and flood-envelope approaches for flood hazard can be readily applied to ice-related floods, and hydrotechnical approaches based on an improved understanding of river-ice processes have been developed. In this paper, the nature and severity of ice-jam flooding, the present status of delineating ice-related flood events, and challenges to delineating ice-related floods are discussed.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| 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".