{"id":"W4381336028","doi":"10.3390/eng4020099","title":"Improved Structural Health Monitoring Using Mode Shapes: An Enhanced Framework for Damage Detection in 2D and 3D Structures","year":2023,"lang":"en","type":"article","venue":"Eng—Advances in Engineering","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Structural health monitoring; Sensitivity (control systems); Computer science; Reliability (semiconductor); Mode (computer interface); MATLAB; Stiffness; Algorithm; Data mining; Reliability engineering; Structural engineering; Engineering; Electronic engineering; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002403181,0.0003554071,0.0004084871,0.0005491892,0.0001084644,0.00005232937,0.0002000054,0.0002027789,0.000001160172],"category_scores_gemma":[0.0001417282,0.0004046194,0.00003513622,0.0006221341,0.0000223253,0.0008061058,0.00005174982,0.0006061427,1.68733e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005505798,"about_ca_system_score_gemma":0.0000196322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001096895,"about_ca_topic_score_gemma":0.00009473907,"domain_scores_codex":[0.9981138,0.0000265298,0.0005049459,0.000416557,0.0001541433,0.000784023],"domain_scores_gemma":[0.9993099,0.0002249418,0.00006869515,0.000232552,0.00002367158,0.0001402572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001841702,0.00000151351,0.0005301762,0.0007725621,0.000005448815,0.00000220342,0.001153745,0.8717467,0.02392712,0.0001398242,1.343912e-7,0.1017022],"study_design_scores_gemma":[0.0003072772,0.00007552405,0.01782824,0.000396041,0.000002919915,0.000004236145,0.000264394,0.943219,0.03406677,0.0034302,0.00002719973,0.0003782077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.852433,0.001452149,0.1426749,0.000004931557,0.001692109,0.0005284421,0.00001341992,0.001198799,0.000002278544],"genre_scores_gemma":[0.8408843,0.0007059157,0.1576974,0.000003613693,0.0004783054,0.0001252105,0.000005914405,0.00009867503,6.058579e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.101324,"threshold_uncertainty_score":0.9998406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01788127393467157,"score_gpt":0.3481964602246475,"score_spread":0.3303151862899759,"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."}}