Sea Dyke Rehabilitation and Climate Change in Dutch and Japanese Contexts
Bibliographic record
Abstract
The purpose of this paper is to analyze the relationship between climate change and the need to rehabilitate sea dykes. Sea dykes are a critical component of coastal infrastructure and national flood prevention systems and are increasingly susceptible to a number of failure mechanisms under climate change conditions. This paper will explore case studies of sea dyke rehabilitation and climate change in both the Netherlands and Japan. Both countries have urban areas within close proximity to coastal areas and have constructed sea and river dykes as part of their national flood prevention plans. The International Panel on Climate Change published a report in February 2012 stating that mean global temperatures are going to increase by 1 to 3 degrees Celcius by 2050, which will affect global weather conditions. The characteristics of climate change which most affect sea dykes include the frequency and severity of storms as well as global sea level rise. These trends increase the risk of dyke failure modes such as overtopping, micro instability, and erosion of non-reinforced inner slopes. Techniques for rehabilitation both proven and proposed will be discussed with a particular focus on methods for implementation as well as the policy framework of these projects.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".