Shoreline bluff failures: A GIS assessment of susceptibility and risk for Lake Erie's north central shore (Ontario)
Bibliographic record
Abstract
One of the characteristic features of the north shore of Lake Erie is its steep, eroding bluffs. Combined with an increase in human presence and pressures at the shoreline, the failure of these slopes has become hazardous. Over the past two decades alone, slope failures have been responsible for millions of dollars of damage to shoreline property, as well as the deaths and near deaths of a number of individuals. Despite the seriousness of this hazard, few studies have identified specific hazard areas and their associated risk of failure along Lake Erie's north shore, and other reaches in the Great Lakes. As a critical foundation to research described in the latter half of the thesis, this paper includes a lengthy, yet necessary, review of literature which is relevant to coastal slope failures. The nature, contributory factors, hazards and risks of coastal bluff failures are discussed. in addition to their occurrence within a global, and local context. Particular attention is given to the shorelines of the Great Lakes and Lake Erie. The literature review then examines methods of mitigating the bluff hazards and risks, including the use and benefits of Geographical Information Systems (GIS) and hazard zone mapping. The focus of the paper is a description of GIS research recently conducted on the bluffs which line Erie’s northern shore between Port Burwell and Long Point, Ontario. Canada. The study utilizes a GIS to analyse factors which contribute to the bluff failures, and ultimately. To estimate the variance in risk to these shoreline failures, emphasis is placed upon the methods used to conduct this research, but a discussion of exploratory analysis, results, recommendations, and conclusions is also provided. Since the hazard of bluff failures exists far beyond the borders of this study site, Lake Erie or even the Great Lakes, the methods presented in the paper will provide a useful framework for conducting similar analyses on other coastlines subject to the hazards of bluff failure. The results of the report will be used to educate the public and governing bodies of the hazards and risks along the study reach, as a means of reducing this risk, including the future loss of lives.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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 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".