An overview of the applications for early warning and mapping of the flood events in New Brunswick
Bibliographic record
Abstract
This paper gives an overview of the on-line flood warning implementation in the province of New Brunswick, Canada. The on-line flood warning applications are available via the "River Watch" website provided by the New Brunswick Department of Environment. Advanced GIS technology combined with hydrological modelling, provide a mapping and visualization tool that can be used by emergency managers and the general public to predict possible flood zones. The applications developed for "River Watch" support the processing of large amounts of digital terrain and hydrological data, which are then, quantified and displayed on digital maps allowing decision makers and the general population to comprehend and visualize the possible area and impact of the flooding. The WebGIS applications that are available from the "River Watch" web site provide snow reports and maps, flood warnings and interactive maps. The searchable historical database containing reports about the impact of past floods and estimated damages provides a valuable insight into the past of the province of New Brunswick and the motivation for development of the system for flood prediction and management.
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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 | 0.000 |
| 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 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".