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Record W1827652896 · doi:10.1260/1369433011502408

Design of RC Columns Subjected to Safety Constraint

2001· article· en· W1827652896 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

VenueAdvances in Structural Engineering · 2001
Typearticle
Languageen
FieldDecision Sciences
TopicProbabilistic and Robust Engineering Design
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsReliability (semiconductor)Constraint (computer-aided design)Reliability engineeringProbabilistic logicStructural engineeringCode (set theory)Probabilistic designOptimal designComputer scienceStructural reliabilityMathematical optimizationEngineeringEngineering design processMathematicsMechanical engineering

Abstract

fetched live from OpenAlex

Minimum cost design of reinforced concrete columns subjected to reliability constraints is a multi-level optimization problem because both the analysis of minimum cost design, and the estimation of the reliability are nonlinearly constrained optimization problems. A procedure for reliability constrained optimal design of columns is described in this study. It seems that such a design approach is allowed by the current CSA A23.3–94 design code and will become more relevant for an objective-based design code. This design approach ensures that the designed columns meet specified reliability levels, and that the construction materials having probabilistic characterizations which are different from those used for design code calibrations are used economically. The procedure is demonstrated through example designs of short and slender columns.

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)0.003
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 score0.819
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 science0.0010.000
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 head0.033
GPT teacher head0.312
Teacher spread0.279 · 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