FIELD MEASUREMENTS OF TSUNAMI EVACUATION DYNAMICS
Bibliographic record
Abstract
The Cascadia Subduction Zone (CSZ) threatens Vancouver Island, Canada, with a significant risk of near- field tsunamis. Both oral history and geological records (Ludwin et al., 2005) document the last major CSZ tsunami event in the year 1700. To mitigate the loss of life during tsunami events, soft measures, such as evacuation planning, have been suggested (Shibayama et al., 2013). Considering that Vancouver Island is expected to face wave arrival times within 20 minutes for a CSZ tsunami (Takabatake et al., 2019), detailed and accurate evacuation planning is essential. Agent-based models (ABMs) have been recommended in preference to Geographic Information Systems (GIS) when performing evacuation assessments as they can portray evacuation dynamics more realistically (Kim et al., 2022). While tsunami evacuation ABMs have been used to assess life safety for multiple coastal communities (Mas et al., 2015), there is a significant lack of data on tsunami evacuation behaviour to inform and calibrate these ABMs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".