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Record W2909942455

Aversion and Warning Factors for Assessing Existing Reinforced Concrete Structures

2018· article· en· W2909942455 on OpenAlexaboutno aff
Marcie van Weerdhuizen

Bibliographic record

VenueScholarship@Western (Western University) · 2018
Typearticle
Languageen
FieldEngineering
TopicFire effects on concrete materials
Canadian institutionsnot available
Fundersnot available
KeywordsForensic engineeringReinforced concreteEngineeringStructural engineering
DOInot available

Abstract

fetched live from OpenAlex

In a world of aging infrastructure, sustainability initiatives require additional investment in the assessment of existing reinforced concrete structures. Reliability-based assessment should minimize costs by reducing conservatism, while ensuring levels of safety equivalent to those for new designs. Current Canadian and US provisions assign target reliability levels for structural assessment based on criteria including occupancy type, expected failure behaviour, and the effect of element failure on the overall structural integrity. These criteria are defined using discrete and qualitative parameter values. It is shown that the true structural conditions can be better represented by verifying the applicability and completeness of these parameters and associating them with quantifiable structural attributes. Structural risk can be quantified by determining the number of people at risk due to an element failure, and by using the magnitude of deflection at incipient failure as an indicator of the warning of failure. Flexural capacities for assessment can be increased by up to 60% of values used for design using reduction factors calibrated to these parameters.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score1.000

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 communication0.0010.002
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 head0.080
GPT teacher head0.311
Teacher spread0.230 · 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.

Study designObservational
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

Citations1
Published2018
Admission routes1
Has abstractyes

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