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Wood Frame Building Response to Rapid-Onset Flooding

2010· article· en· W2157541315 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueNatural Hazards Review · 2010
Typearticle
Languageen
FieldEngineering
TopicEarthquake and Tsunami Effects
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFlood mythFlooding (psychology)Natural disasterShoreFrame (networking)Natural hazardEmergency responseCivil engineeringNatural (archaeology)Forensic engineeringEnvironmental scienceEnvironmental resource managementEngineeringGeographyGeologyMeteorology

Abstract

fetched live from OpenAlex

Floods are considered to be among the deadliest, costliest, and most common natural disasters. Rapid-onset, catastrophic floods inundate the shore quickly and manifest as deep water with high velocities, inflict great pressures and forces on the built and natural environments, and pose a threat to human safety. Current building codes, design practices, and disaster planning methods account for potential earthquake and wind loads on simple wood-frame buildings typical of North American residential construction. However, flood impacts have not been considered to the same degree of detail. A theoretical model is developed that describes flood impacts on wood-frame residential buildings and relates building response to flood depth and velocity. The failure mechanisms considered and the model logic are described and applied to assess the response of a typical Canadian wood-frame home to flood conditions that might be experienced in a rapid-onset flood event.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.942
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.006
GPT teacher head0.262
Teacher spread0.256 · 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