{"id":"W2782665410","doi":"10.3390/geosciences8010016","title":"Earthquake Magnitude and Shaking Intensity Dependent Fragility Functions for Rapid Risk Assessment of Buildings","year":2018,"lang":"en","type":"article","venue":"Geosciences","topic":"Seismic Performance and Analysis","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada; École de Technologie Supérieure","funders":"","keywords":"Fragility; Magnitude (astronomy); Spectral acceleration; Intensity (physics); Earthquake scenario; Seismic risk; Seismology; Vulnerability assessment; Vulnerability (computing); Environmental Seismic Intensity scale; Seismic hazard; Incremental Dynamic Analysis; Geology; Peak ground acceleration; Computer science; Ground motion; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004521685,0.00006830148,0.0001258488,0.0000796069,0.0002034066,0.00003323901,0.00009753895,0.00002577622,0.00004314348],"category_scores_gemma":[0.00003907014,0.00005719733,0.0000405985,0.0001885303,0.0001736285,0.0001873115,0.00003331049,0.00005976216,0.000002163852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001342904,"about_ca_system_score_gemma":0.00001526496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001943576,"about_ca_topic_score_gemma":0.0001445687,"domain_scores_codex":[0.9993988,0.000006701753,0.0001409114,0.0001589975,0.0001330255,0.0001615663],"domain_scores_gemma":[0.9996811,0.00003427263,0.00004157679,0.0001093107,0.00009556334,0.00003824283],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001590702,0.00006273702,0.6488915,0.0001238021,0.0001289351,6.592567e-7,0.0008850336,0.004445295,0.01055112,0.0001115217,0.0009658979,0.3338176],"study_design_scores_gemma":[0.0001752622,0.0001475352,0.585606,0.00002069996,0.0000677492,0.000002767596,0.0007525469,0.4039171,0.003027837,0.0002211895,0.005924918,0.0001362967],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9248387,0.0001055173,0.07419483,0.00002777471,0.0002450077,0.00007397113,0.00002141244,0.00004060884,0.0004522422],"genre_scores_gemma":[0.9952003,0.0001294651,0.00450534,0.0000394232,0.00007236556,0.00001246553,0.000001955282,0.000003004705,0.00003565142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3994718,"threshold_uncertainty_score":0.2332439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01290559472518939,"score_gpt":0.2536976740196844,"score_spread":0.240792079294495,"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."}}