{"id":"W2114858213","doi":"10.1002/eqe.2513","title":"Record selection for aftershock incremental dynamic analysis","year":2014,"lang":"en","type":"article","venue":"Earthquake Engineering & Structural Dynamics","topic":"Seismic Performance and Analysis","field":"Engineering","cited_by":77,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of British Columbia; Alexander von Humboldt-Stiftung","keywords":"Aftershock; Fragility; Geology; Seismology; Selection (genetic algorithm); Computer science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001208218,0.0002894751,0.0003650929,0.0004264404,0.00009423842,0.00006926973,0.0001647426,0.0001079489,0.00004339637],"category_scores_gemma":[0.00002339853,0.0003025765,0.0002976747,0.0008468711,0.00001446201,0.0002194355,0.00001943789,0.0001947156,0.00001152125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002198781,"about_ca_system_score_gemma":0.000006303397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003937486,"about_ca_topic_score_gemma":0.0005255427,"domain_scores_codex":[0.998808,0.000009838052,0.0003246828,0.0002629887,0.0001640759,0.000430413],"domain_scores_gemma":[0.9995551,0.0000502503,0.00004271452,0.0002162908,0.00004304166,0.00009262841],"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":[0.00001120343,0.000002977426,0.00856857,0.00008571445,0.0007785389,3.800203e-7,0.00007216955,0.7089364,0.0009011496,0.0001441638,0.00003270626,0.280466],"study_design_scores_gemma":[0.0002020573,0.00003442051,0.2168638,0.000008668427,0.0002670154,0.000003681157,0.00001647856,0.7815238,0.00008065244,0.00003425621,0.0006736655,0.000291502],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7189617,0.00002749668,0.2800725,0.00001725673,0.000352051,0.0001001456,0.00003346884,0.0003923507,0.00004305307],"genre_scores_gemma":[0.992358,0.00002019218,0.006887848,0.00002927937,0.0001516752,0.00002996221,0.0003353253,0.0000549928,0.0001327295],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2801745,"threshold_uncertainty_score":0.9999427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002822821323970316,"score_gpt":0.1901383694722846,"score_spread":0.1873155481483143,"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."}}