{"id":"W2011194523","doi":"10.1007/s13349-013-0040-9","title":"Developing a pattern-based method for detecting defective sensors in an instrumented bridge","year":2013,"lang":"en","type":"article","venue":"Journal of Civil Structural Health Monitoring","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Structural health monitoring; Bridge (graph theory); Strain gauge; Pier; Sensitivity (control systems); Data mining; Matching (statistics); Reliability (semiconductor); Computer science; Autoregressive model; Structural engineering; Engineering; Finite element method; Electronic engineering; Mathematics; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003689841,0.0004434399,0.0004119496,0.0008649543,0.0002154458,0.000498691,0.001046104,0.0009122121,0.001211995],"category_scores_gemma":[0.00102136,0.0003452422,0.0003079089,0.0005449075,0.0002645451,0.0006158868,0.0004236696,0.0004322011,0.0005077965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002160382,"about_ca_system_score_gemma":0.0004283348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00103993,"about_ca_topic_score_gemma":0.001791195,"domain_scores_codex":[0.9996873,0.00003129915,0.00001626177,0.00007401555,0.0001723651,0.00001881876],"domain_scores_gemma":[0.9993578,0.0001619656,0.0000666265,0.00007776565,0.0003139861,0.0000219143],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001328175,0.0001289063,0.002724036,0.0001428314,0.00004220889,0.0001570886,0.0000897412,0.01051166,0.5398075,0.001053434,0.0007549493,0.4444548],"study_design_scores_gemma":[0.00003518114,0.0002729419,0.005432534,0.0000154918,0.00006208659,0.0008381254,0.00007494231,0.7271109,0.2622685,0.0009492189,0.002908389,0.00003172721],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03761021,0.0000851712,0.960737,0.00004166361,0.00003648507,0.00005906319,0.00003543215,0.0007074533,0.0006876263],"genre_scores_gemma":[0.2159998,0.0001297785,0.7815179,0.00004969354,0.00001936415,0.00007426124,0.00007956006,0.00005133825,0.002078308],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001211995,"threshold_uncertainty_score":0.004054546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0489700347383145,"score_gpt":0.3724341255924959,"score_spread":0.3234640908541814,"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."}}