{"id":"W4399895119","doi":"10.3390/app14125350","title":"Investigation of Structural Seismic Vulnerability Using Machine Learning on Rapid Visual Screening","year":2024,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Seismology and Earthquake Studies","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Vulnerability (computing); Computer science; Artificial intelligence; Computer security","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009690871,0.0001130206,0.0001449265,0.000159863,0.0005692756,0.0001085261,0.0003485308,0.00004194838,0.00001116399],"category_scores_gemma":[0.00004457809,0.0000873162,0.00003848156,0.0007835582,0.000597993,0.0002865692,0.0001460457,0.0002140604,0.000007834202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001334324,"about_ca_system_score_gemma":0.0000686038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009539189,"about_ca_topic_score_gemma":0.000004281749,"domain_scores_codex":[0.9987732,0.00009114399,0.0001914948,0.0004339452,0.0002899187,0.0002203239],"domain_scores_gemma":[0.9994653,0.0002927425,0.0000637676,0.0001170676,0.00002277085,0.00003835034],"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":[0.00004871141,0.00002166045,0.08065281,0.000175542,0.000129964,0.00001871408,0.01329692,0.1885745,0.07178512,0.2594154,0.00007565384,0.385805],"study_design_scores_gemma":[0.00007653895,0.0001454053,0.01394072,0.00003047835,0.000005975131,0.000008926901,0.0001606291,0.9542226,0.01979928,0.01139031,0.00009087018,0.0001282499],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9255236,0.0003976618,0.07259412,0.000419818,0.0002815746,0.00007906968,7.349262e-7,0.0001280008,0.0005753493],"genre_scores_gemma":[0.9836366,0.000003316209,0.01608671,0.0002078726,0.00004643917,0.000002903687,0.000001121312,0.000003078939,0.00001193059],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7656481,"threshold_uncertainty_score":0.4378465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05224834362512428,"score_gpt":0.2990121197542804,"score_spread":0.2467637761291561,"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."}}