{"id":"W4400163651","doi":"10.31224/3763","title":"Fast Probabilistic Seismic Hazard Analysis through Adaptive Importance Sampling","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"York University","keywords":"Probabilistic logic; Hazard; Computer science; Sampling (signal processing); Seismic hazard; Seismology; Importance sampling; Statistics; Geology; Mathematics; Artificial intelligence; Monte Carlo method; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009944987,0.0006698482,0.0006246816,0.00100645,0.0002970621,0.0007661734,0.001266774,0.0004776767,0.002182968],"category_scores_gemma":[0.004668137,0.000441734,0.0006044691,0.0007230355,0.0004718186,0.0009416012,0.001164121,0.0009794977,0.0003647766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006912648,"about_ca_system_score_gemma":0.001050176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006727468,"about_ca_topic_score_gemma":0.007169567,"domain_scores_codex":[0.9995546,0.0001247461,0.0000160153,0.00005749907,0.0002018641,0.0000452963],"domain_scores_gemma":[0.9981803,0.001183128,0.0001450093,0.0001737526,0.0002376084,0.00008022071],"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":[0.0000741293,0.00003673518,0.00294398,0.00004520634,0.00004223518,0.00006408618,0.00004791998,0.9174007,0.00213612,0.01093263,0.00124378,0.06503248],"study_design_scores_gemma":[0.000003507876,0.000003397681,0.00008599044,0.000001002983,0.000001204993,0.000006120184,0.000002462557,0.9972034,0.000177953,0.002388374,0.0001252648,0.000001508802],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02258363,0.0001059968,0.9750107,0.000079119,0.00001539557,0.00003376037,0.000085219,0.001054334,0.001031866],"genre_scores_gemma":[0.623621,0.0001414064,0.3738941,0.00008822521,0.00006503954,0.0001253909,0.0005103968,0.0002114595,0.00134297],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006727468,"threshold_uncertainty_score":0.01337659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0432014281823409,"score_gpt":0.303925497325348,"score_spread":0.2607240691430071,"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."}}