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Hydrodynamic and loss of life modelling for the 1953 Canvey Island flood

2008· book-chapter· en· W8909656 on OpenAlexfundno aff
Manuela Di Mauro, Darren Lumbroso

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicFlood Risk Assessment and Management
Canadian institutionsnot available
FundersBC Hydro
KeywordsFlood mythGeographyEnvironmental scienceArchaeology

Abstract

fetched live from OpenAlex

Canvey Island is located in the Thames Estuary. The island is a low-lying alluvial fan covering an area of 18.5 km2, with an average height of approximately 1 m below the mean high water level. Canvey Island is protected against inundation by a network of flood defences. In 1953, the island was inundated by the “Great North Sea Flood” that breached the island’s flood defences and resulted in the deaths of 58 people and the destruction of several hundred houses. As part of the EC funded research project FLOODsite, work was undertaken to set up both a hydrodynamic and an agent-based loss-of-life model of Canvey Island for the 1953 flood. The objective of the work was to obtain a better understanding of the 1953 flood event and to analyse the consequences of breaches in the island’s flood defences in terms of loss of life and injuries. The work undertaken indicates that the agent-based life safety model can provide a scientifically robust method to assess loss of life, injuries and evacuation times for areas that are at risk from flooding in the UK.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.199
Teacher spread0.184 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations23
Published2008
Admission routes1
Has abstractyes

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