High water levels in Big Lake, caused by Hurricane Dorian (Sept. 7, 2019) and changes to Long Beach, Nova Scotia
Bibliographic record
Abstract
Hurricane Dorian in September 2019 provided the first opportunity, since the present tidal channel opened through Long Beach in March 2019, to observe the impacts of storm generated waves and water level fluctuations along the inner shores of Big Lake. In-situ water pressure and CTD recording gauges within Big Lake provided new insights into changes in hydrology that are occurring. The accelerated deterioration of Long Beach in 2018 and 2019 and its response to the presence of an inlet marks a new phase in its evolution, which may have begun 20 years ago and possibly marks the renewal of a phase of barrier instability that prevailed before 1945. Hurricane Dorian produced record water levels of 2.6-2.8 m (CGVD28) in Big Lake when it was tidal compared with 2.2 m (CGVD28) when it was non-tidal during Hurricane Juan (2003). In 2019, shore infrastructure along the exposed northern shores of Big Lake was damaged by strong easterly winds and waves that coincided with high tide. Waves extended onshore to a maximum elevation of 3.04 m (CGVD28). This elevation provides a basis for mapping flood hazards along this shore at present sea level. In contrast, wave run-up of 4.0 m was measured along the outer shore at Long Beach. Therefore, while the tidal inlet allowed the storm surge into the lake, the beach continued to protect inland properties against wave action during Hurricane Dorian. However, longshore changes to its crest elevation have caused differential landward shore migration. Physical response to future storms along each of the three segments of Long Beach will be different as each segment migrates landward. For the near future, the western barrier should provide the best protection for inland properties against wave attack however, with projected rises in sea level, natural stress on the barrier will continue.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 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".