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Effect of seawalls on tsunami evacuation departure in the 2011 Great East Japan Earthquake

2018· article· en· W2900939352 on OpenAlexaff
Giancarlos Parady, Bryan Tran, Stuart Gilmour

Bibliographic record

VenueInjury Prevention · 2018
Typearticle
Languageen
FieldEngineering
TopicEvacuation and Crowd Dynamics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSeawallPreparednessPoison controlWork (physics)Forensic engineeringOccupational safety and healthEngineeringMedical emergencyMedicinePolitical scienceGeotechnical engineering

Abstract

fetched live from OpenAlex

OBJECTIVE: To quantitatively evaluate the effect of seawalls on tsunami evacuation departure. METHODS: A mixed-effect Cox proportional-hazards regression model was applied to evacuation behavioural data obtained from a probability survey of survivors of the 2011 Great East Japan Earthquake and Tsunami in Iwate and Miyagi prefectures. FINDINGS: Presence of a seawall higher than the forecast tsunami height at any given time reduces the likelihood of prompt evacuation by 30%. Findings suggest the existence of a false sense of security among residents deriving from the presence of seawalls. CONCLUSION: Prompt evacuation is a key factor affecting survival. The effect of seawalls on evacuation decisions is an important policy consideration. More work is needed in disaster preparedness education and in the way tsunami warnings are given, taking into consideration the risk of forecast error. Priority should be given to promoting prompt evacuation and educating residents as to the uncertainty of tsunami forecasting, to ensure that residents do not ignore evacuation warnings due to false impressions of the safety provided by seawalls.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.901
Threshold uncertainty score0.357

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.270
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2018
Admission routes1
Has abstractyes

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