{"id":"W4404253200","doi":"10.1007/978-981-97-7043-4_53","title":"Seismic Zone Clustering and Risk Prediction Using AI/ML and GIS Techniques","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in civil engineering","topic":"Seismology and Earthquake Studies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carbon Engineering (Canada)","funders":"","keywords":"Cluster analysis; Computer science; Geology; Data mining; Seismology; Geography; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001871303,0.0003510946,0.0003463442,0.0003911225,0.00009016853,0.00009682409,0.0001490911,0.0004048987,0.000003690437],"category_scores_gemma":[0.00004856236,0.0003511593,0.00004772546,0.00008876668,0.00006144205,0.0001567333,0.0003887222,0.0009184171,0.000001786398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006357773,"about_ca_system_score_gemma":0.00001656971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007511361,"about_ca_topic_score_gemma":0.0002298505,"domain_scores_codex":[0.9988317,0.000009082399,0.0002442602,0.0005406413,0.0001189492,0.0002553822],"domain_scores_gemma":[0.9994625,0.0001529126,0.0000589743,0.0002572703,0.00002272238,0.00004560851],"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":[0.00002487438,0.00001604247,0.002231083,0.001969957,0.0008120402,0.0004359952,0.005753909,0.5696376,0.0007632959,0.01004042,0.00009214495,0.4082226],"study_design_scores_gemma":[0.0001110445,0.00007119693,0.0004912245,0.001086531,0.00007807367,0.0002995906,0.000001388128,0.9720855,0.0002566699,0.01620833,0.008866955,0.0004434971],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00117826,0.009914935,0.9859515,0.0002441353,0.0006032843,0.0001697849,0.00001332586,0.0004503676,0.001474347],"genre_scores_gemma":[0.9407306,0.004570381,0.05251035,0.0002523828,0.000654513,0.00002220219,0.00000712067,0.0001248763,0.001127518],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9395524,"threshold_uncertainty_score":0.999894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008599827728195383,"score_gpt":0.2083580990085225,"score_spread":0.1997582712803271,"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."}}