{"id":"W4385660882","doi":"10.1007/s41062-023-01199-2","title":"Multidimensional tensor strategy for the inverse analysis of in-service bridge based on SHM data","year":2023,"lang":"en","type":"article","venue":"Innovative Infrastructure Solutions","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Henan University of Technology","keywords":"Data mining; Computer science; Sample (material); Data set; Set (abstract data type); Data quality; Structural health monitoring; Statistic; Data analysis; Data science; Service (business); Statistics; Mathematics; Engineering; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.0003625705,0.0001953719,0.0002887275,0.000883613,0.0001764126,0.00001474549,0.0004707393,0.0001246283,0.00003109506],"category_scores_gemma":[0.0002527284,0.0001523664,0.00005327736,0.007973154,0.0001132684,0.0001235947,0.0001234226,0.0003449653,0.000003744731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001449399,"about_ca_system_score_gemma":0.0001300761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002551692,"about_ca_topic_score_gemma":0.0005278005,"domain_scores_codex":[0.9986507,0.00003666145,0.0004426966,0.0002781927,0.000230401,0.0003613745],"domain_scores_gemma":[0.9979907,0.0006793715,0.00009620419,0.0007828472,0.0004139197,0.00003696979],"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":[0.00003862652,0.00001341058,0.006233473,0.0000835689,0.0003214341,0.000001919597,0.0002610008,0.9643747,0.00147982,0.002796217,0.01853015,0.005865651],"study_design_scores_gemma":[0.0001597767,0.00002218489,0.4793684,0.00002117428,0.00004777222,2.533939e-7,0.00006726222,0.5186641,0.0002238216,0.0003596014,0.0009821925,0.00008352378],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9728685,0.0000345632,0.01916273,0.001117509,0.0008994466,0.001100256,0.003867814,0.0007616018,0.0001875521],"genre_scores_gemma":[0.9910742,0.00000720442,0.007721684,0.0002153996,0.00008726148,0.00008620277,0.0007754581,0.00002699552,0.000005562801],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4731349,"threshold_uncertainty_score":0.6213323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1104705018942114,"score_gpt":0.359463376270419,"score_spread":0.2489928743762075,"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."}}