{"id":"W4409994676","doi":"10.1177/87552930251321301","title":"Modeling post‐earthquake functional recovery of bridges","year":2025,"lang":"en","type":"article","venue":"Earthquake Spectra","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Pacific Earthquake Engineering Research Center, University of California Berkeley; National Science Foundation","keywords":"Duration (music); Bridge (graph theory); Closure (psychology); Resilience (materials science); Engineering; Component (thermodynamics); Computer science; Reliability engineering; Transport engineering; Civil engineering","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":[0.0006032449,0.0005587206,0.0003678073,0.0007206842,0.0004427173,0.0007426083,0.00123967,0.001399412,0.002114397],"category_scores_gemma":[0.001348298,0.0003692815,0.0008448255,0.0004626997,0.0006240475,0.0007789703,0.000920283,0.0006150535,0.0002008582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001652548,"about_ca_system_score_gemma":0.001662649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04442302,"about_ca_topic_score_gemma":0.0309274,"domain_scores_codex":[0.9997842,0.0000572844,0.00001040201,0.00004788569,0.00002917451,0.00007112264],"domain_scores_gemma":[0.9996651,0.0001486606,0.00006722713,0.00002332872,0.00006378804,0.0000318843],"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":[0.000006468651,0.00001151771,0.000582036,0.000004919575,0.000005093234,0.00001781371,0.00001669631,0.9965326,0.0002491624,0.001743647,0.00005275088,0.0007772297],"study_design_scores_gemma":[0.000002188639,0.00001328169,0.0004659607,0.000002855068,0.000004278018,0.000005594346,0.00002329569,0.9983133,0.0001213087,0.0008265729,0.0002181452,0.000003162561],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7193729,0.0003117681,0.2575964,0.0005746445,0.00004426769,0.000155232,0.001172761,0.0004002681,0.02037175],"genre_scores_gemma":[0.9847533,0.0001589812,0.01107958,0.00002327347,0.000007442559,0.0001109743,0.0003015015,0.00003229772,0.003532637],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04442302,"threshold_uncertainty_score":0.0883289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006794059537440654,"score_gpt":0.2068940885189514,"score_spread":0.2001000289815107,"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."}}