{"id":"W2037022103","doi":"10.1061/(asce)0733-9399(2004)130:2(142)","title":"Damage Detection Utilizing the Damage Index Method to a Benchmark Structure","year":2004,"lang":"en","type":"article","venue":"Journal of Engineering Mechanics","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":78,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of British Columbia; Texas A and M University","keywords":"Benchmark (surveying); Structural health monitoring; Modal; Identification (biology); Computer science; Stiffness; Eigenvalues and eigenvectors; Task (project management); Structural engineering; Data mining; Algorithm; Engineering; Materials science; Physics; Geology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005794714,0.0004923369,0.0005509537,0.0008929461,0.0002746452,0.0004020915,0.0005281966,0.0006933609,0.0006565073],"category_scores_gemma":[0.003539008,0.0001458327,0.000244346,0.0004521089,0.000410262,0.0005049064,0.0006141443,0.0004705021,0.0001231451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004843417,"about_ca_system_score_gemma":0.0002918124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002088302,"about_ca_topic_score_gemma":0.002285947,"domain_scores_codex":[0.9996967,0.00008805261,0.00001042899,0.00005996209,0.0001093695,0.00003540578],"domain_scores_gemma":[0.9992331,0.0003796274,0.0001004768,0.00008068155,0.0001595865,0.00004637957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002736512,0.0001570037,0.003699542,0.0001059608,0.00003201899,0.0002038346,0.0001213553,0.8052937,0.05160771,0.007518377,0.0007289284,0.130258],"study_design_scores_gemma":[0.00000371642,0.00007696384,0.0007255709,0.000002689847,0.00000250468,0.00003711806,0.00001114983,0.9933017,0.004476517,0.001115756,0.0002421593,0.000004147611],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.30271,0.0002152582,0.6936493,0.0001176004,0.00003131152,0.00006228751,0.00009259382,0.0003213178,0.002800348],"genre_scores_gemma":[0.8765233,0.0001244971,0.1214402,0.00002744129,0.00001684694,0.00004447772,0.0001360305,0.00002740977,0.001659908],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002088302,"threshold_uncertainty_score":0.004152298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01034537154288859,"score_gpt":0.266658174521398,"score_spread":0.2563128029785094,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}