Highwater Mark Collection after Post Tropical Storm Dorian and Implications for Prince Edward Island, Canada
Bibliographic record
Abstract
Prince Edward Island (PEI), Canada has been experiencing the consequences of a rising sea level and intense storms on its coasts in recent years. The most recent severe event, Post Tropical Storm Dorian (Dorian), began impacting Prince Edward Island on 7 September 2019 and lasted for over 20 h until the morning of 8 September 2019. The measurement of highwater marks (HWM) from the storm was conducted between 25 September and 25 October 2019 using a high precision, survey grade methodology. The HWM measured included vegetation lines, wrack lines, beach, cliff, and dune morphological features, and tide gauge data at 53 locations in the Province along coastal areas that are exposed to high tides, storm surge, high winds, and wave runup. Photos were taken to provide evidence on the nature of the HWM data locations. The data reveal that Dorian caused extensive coastal floods in many areas along the North and South Coast of Prince, Queens and Western Kings Counties of Prince Edward Island. The floods reached elevations in excess of 3.4 m at some locations, posing threats to local infrastructure and causing damage to natural features such as sand dunes in these areas. The HWM data can provide useful information for community and emergency response organizations as plans are developed to cope with the rising sea level and increased frequency of highwater events as predicted by researchers. As Dorian has caused significant damage in several coastal areas in PEI, better planning using an enhanced storm forecasting and coastal flood warning system, in conjunction with flood stage values, could possibly have reduced the impacts of the storm in the impacted areas. This could help enhance public understanding of the potential impacts in local areas and how they can prepare and adapt for these events in the future.
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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) | 0.001 | 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".