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Computer Program for Multimodel Reliability and Optimization Analysis

2012· article· en· W2039638270 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.

Bibliographic record

VenueJournal of Computing in Civil Engineering · 2012
Typearticle
Languageen
FieldDecision Sciences
TopicProbabilistic and Robust Engineering Design
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaKillam Trusts
KeywordsComputer scienceReliability (semiconductor)Scripting languageComputer programComputationProgram analysisProbabilistic logicSoftwareReliability engineeringDistributed computingArtificial intelligenceEngineeringProgramming language

Abstract

fetched live from OpenAlex

A computer program is developed to carry out reliability and optimization analysis with many interconnected probabilistic models. The program is freely available online and it contains a library of versatile models. The user can also implement new models—without any recompilation of the program—by several means, including a powerful scripting option. Other novel features include a comprehensive parameterization that facilitates flexible and effective model communication and the computation of direct-differentiation response sensitivities in multimodel analysis. The new program has already been successfully employed for regional risk analysis with thousands of model objects and hundreds of random variables. This paper presents the software architecture and a multimodel example of a structure that is modeled in an external finite-element program and subjected to multiple hazards, damage, and long-term deterioration.

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)0.005
metaresearch head score (Gemma)0.002
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: Methods · Consensus signal: none
Teacher disagreement score0.454
Threshold uncertainty score0.393

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.042
GPT teacher head0.324
Teacher spread0.282 · 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