{"id":"W4236424449","doi":"10.1007/978-3-0348-8179-1_19","title":"Application of Kalman Filtering Techniques for Microseismic Event Detection","year":2002,"lang":"en","type":"book-chapter","venue":"Birkhäuser Basel eBooks","topic":"Seismology and Earthquake Studies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Read Jones Christoffersen (Canada)","funders":"","keywords":"Microseism; Geology; Induced seismicity; Noise (video); Seismology; Event (particle physics); Ambient noise level; Real-time computing; Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007803348,0.0008054889,0.0006290555,0.001006406,0.0004196951,0.000701005,0.0005619017,0.0007922737,0.00166979],"category_scores_gemma":[0.002481055,0.0004587443,0.0006108077,0.001071029,0.0002567598,0.0009399448,0.0005106085,0.0009160942,0.0009713952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004364773,"about_ca_system_score_gemma":0.0007223089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008597361,"about_ca_topic_score_gemma":0.006456741,"domain_scores_codex":[0.9993562,0.0001122413,0.00005869826,0.000182966,0.0002301665,0.00005972517],"domain_scores_gemma":[0.9992383,0.0003673955,0.00007697897,0.00006330982,0.0002380715,0.00001604709],"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":[0.0001852452,0.0000750266,0.002284054,0.0002380051,0.0001623401,0.0001273163,0.0001678256,0.2117248,0.02104169,0.008154417,0.002862096,0.7529772],"study_design_scores_gemma":[0.00001155958,0.00004812091,0.001670731,0.00002454416,0.00002849993,0.00006879388,0.00003158158,0.9838091,0.006219136,0.002772774,0.005288504,0.00002670446],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002265651,0.0001979543,0.9964918,0.00004482929,0.00004048256,0.00001432733,0.00002591939,0.0004412732,0.0004777896],"genre_scores_gemma":[0.2841759,0.001334929,0.7084764,0.0001458426,0.0001228,0.000157914,0.0003251357,0.0001507978,0.005110213],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008597361,"threshold_uncertainty_score":0.01709467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01969454287065414,"score_gpt":0.2323647995875114,"score_spread":0.2126702567168573,"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."}}