INDIAN OCEAN TSUNAMI ON 26 DECEMBER 2004: NUMERICAL MODELING OF INUNDATION IN THREE CITIES ON THE SOUTH COAST OF SRI LANKA
Bibliographic record
Abstract
The 2004 Indian Ocean tsunami caused enormous loss of lives and damage to property in Sri Lanka and in several other countries bordering the Indian Ocean. One way of mitigating potential loss of lives from a similar event in the future is through early warning and quick evacuation of vulnerable coastal communities to safer areas, and such evacuation planning is usually carried out based on inundation maps. Accordingly, the present paper outlines the numerical modelling carried out to develop tsunami inundation maps on a grid of 10 m resolution for three cities on the south coast of Sri Lanka. The results give the tsunami arrival time contours and the spatial distribution of the extent of inundation, the maximum flow velocities as well as the hydrodynamic force in these three cities due to an event similar to the 2004 tsunami.
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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 | 0.001 | 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".