MétaCan
Menu
Back to cohort
Record W2982022166 · doi:10.4095/226357

Fourth-generation seismic hazard maps for the 2005 national building code of Canada

2004· report· en· W2982022166 on OpenAlexaffabout
J Adams, S Halchuk

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsSeismic hazardCode (set theory)Building codeSeismologyHazardComputer scienceGeologyGeographyEngineeringCivil engineeringProgramming languageBiology

Abstract

fetched live from OpenAlex

The Geological Survey of Canada's new seismic hazard model for Canada will form the basis for the seismic design provisions of the 2005 National Building Code of Canada (NBCC). As such it represents Canada's fourth generation of seismic hazard maps (previous ones were in 1953, 1970, and 1985). The Cornell-McGuire method is used with two complete earthquake source models - historical and regional/geological - to represent the uncertainty in where (and why) earthquakes will happen in the future. Ground motions for a deterministic Cascadia subduction earthquake are computed for southwestern Canada, and probabilistic seismic hazard for the nearly aseismic central part of Canada is assessed based on a global model. A 'robust' method is used to combine the probabilistic hazard estimates (at a probability of 2%/50 years or 0.000404 p.a.) from the four source models: the mapped value is the largest of the values. Products will include seismic hazard maps, tabulated values, uniform hazard spectra (UHS), plots of deaggregated hazard and documentation. For the seismic provisions of the 2005 National Building Code of Canada the median ground motion on firm soil sites for spectral acceleration at periods of 0.2, 0.5, 1.0 and 2.0 seconds and peak acceleration will be used. The four spectral parameters will allow the construction of approximate UHS for each locality, and hence improve earthquake-resistant design.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.941
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.028
GPT teacher head0.253
Teacher spread0.224 · 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 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

Citations14
Published2004
Admission routes2
Has abstractyes

Explore more

Same topicSeismic Performance and AnalysisFrench-language works237,207