{"id":"W3123734846","doi":"10.1177/1045389x20983886","title":"Measure point arrangement strategy for in-service continuous girder bridge SHM with consideration of structural robustness (Special Issue of ICAST 2019)","year":2021,"lang":"en","type":"article","venue":"Journal of Intelligent Material Systems and Structures","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Henan University of Technology","keywords":"Robustness (evolution); Structural health monitoring; Girder; Structural engineering; Bridge (graph theory); Span (engineering); Engineering; Measure (data warehouse); Computer science; Data mining","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":[0.000313028,0.0004609971,0.0003068542,0.00048287,0.0003159257,0.0004108578,0.0007373067,0.0004913196,0.003448001],"category_scores_gemma":[0.0003803814,0.0001561021,0.0004056061,0.0002313496,0.0002740619,0.0005314337,0.0008817628,0.0002764392,0.0004720181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003169475,"about_ca_system_score_gemma":0.0002789289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001203021,"about_ca_topic_score_gemma":0.001423636,"domain_scores_codex":[0.9997622,0.00003562606,0.00001380399,0.00004823646,0.0001061891,0.00003384653],"domain_scores_gemma":[0.9998471,0.00001961065,0.00002764136,0.00002738439,0.00005710614,0.00002120489],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003475833,0.000183195,0.009118722,0.0003413907,0.00009356434,0.0007504142,0.0004053207,0.3005338,0.2501441,0.01544241,0.006315379,0.4163241],"study_design_scores_gemma":[0.00002954781,0.0007104091,0.005616102,0.00001584841,0.00006388422,0.0003370121,0.0002374506,0.9534441,0.028143,0.003520732,0.007847974,0.00003390032],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1929243,0.0004492842,0.7933002,0.0002377027,0.0001407157,0.0001292098,0.00006358516,0.0006791443,0.01207594],"genre_scores_gemma":[0.9043154,0.0002048928,0.09098493,0.0000536422,0.00005653304,0.00006246958,0.0001214031,0.0000384846,0.004162224],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003448001,"threshold_uncertainty_score":0.01153475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02748648564596207,"score_gpt":0.2827475550459903,"score_spread":0.2552610694000282,"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."}}