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Record W2330595298 · doi:10.1061/41131(370)25

Key Findings from the Nonlinear Base-Isolated Benchmark

2010· article· en· W2330595298 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.

Bibliographic record

VenueStructures Congress 2010 · 2010
Typearticle
Languageen
FieldEngineering
TopicStructural Health Monitoring Techniques
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBenchmark (surveying)Nonlinear systemKey (lock)Computer scienceMATLABBase (topology)Isolation (microbiology)Scale (ratio)Control (management)Artificial intelligenceMathematicsComputer security

Abstract

fetched live from OpenAlex

Two phases of the benchmark problem on base-isolated buildings concluded recently, culminating in two separate special issues in the Journal of Structural Control and Health Monitoring. The base-isolated building considered in the benchmark problem is based on the USC hospital building in Southern California. The goal of this benchmark is to provide a common computational test-bed to analyze competing control strategies on base-isolated buildings, including devices, algorithms and sensors. To achieve this goal, a 3-D finite-element model was developed in MATLAB to represent the complex behavior of the full-scale base-isolated building with lateral-torsional behavior. The model allows users to model both linear and nonlinear isolation systems. A nonlinear structural analysis tool was developed in MatlabTM and distributed to the participants for nonlinear dynamic analysis. Over twenty papers in two special issues in the Journal of Structural Control and Health Monitoring were published as a result of this effort. This paper presents an overview of this benchmark effort.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.582
Threshold uncertainty score0.980

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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.253
Teacher spread0.243 · 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