{"id":"W3130336953","doi":"10.2749/kualalumpur.2018.0701","title":"Integration of SHM at an early stage in the design and construction of long-span bridges","year":2018,"lang":"en","type":"article","venue":"Report","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bridge (graph theory); Process (computing); Construction engineering; Span (engineering); Structural health monitoring; Stage (stratigraphy); Life span; Engineering; Work (physics); Systems engineering; Computer science; Reinforced concrete; Construction management; Civil engineering; Structural engineering; Mechanical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003218478,0.0003923171,0.000300417,0.0007575221,0.0005838945,0.001320243,0.0007083846,0.0007691343,0.002986937],"category_scores_gemma":[0.00288608,0.0004639034,0.000312198,0.0004872286,0.0007694462,0.001680548,0.001903356,0.0008040185,0.0005783789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001225253,"about_ca_system_score_gemma":0.001952361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00255821,"about_ca_topic_score_gemma":0.00842351,"domain_scores_codex":[0.9969211,0.000797833,0.000149411,0.000211736,0.001634779,0.0002851764],"domain_scores_gemma":[0.9983544,0.0003079247,0.0001730941,0.0004225168,0.0006451342,0.00009695307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002654175,0.0004697255,0.03627846,0.0005723747,0.00006764096,0.0008709097,0.00353587,0.07742988,0.1968847,0.04179674,0.00269587,0.6391324],"study_design_scores_gemma":[0.0000807249,0.005269786,0.1863244,0.0007600569,0.0002322944,0.001755802,0.005562392,0.2601043,0.2714604,0.02790997,0.2403149,0.0002249854],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2604679,0.0005856911,0.6724496,0.0008583769,0.0001195799,0.0004104132,0.00009623772,0.001261584,0.06375065],"genre_scores_gemma":[0.7526008,0.0002546404,0.236229,0.0001279995,0.00003445956,0.0001106983,0.0001191472,0.00008857112,0.0104347],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003218478,"threshold_uncertainty_score":0.01702112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01641450674024481,"score_gpt":0.2475445090611837,"score_spread":0.2311300023209389,"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."}}