{"id":"W2192422974","doi":"10.1190/geo2014-0561.1","title":"Fast and automatic microseismic phase-arrival detection and denoising by pattern recognition and reduced-rank filtering","year":2015,"lang":"en","type":"article","venue":"Geophysics","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Agencia Nacional de Promoción Científica y Tecnológica","keywords":"Microseism; Computer science; Waveform; Algorithm; Context (archaeology); Pattern recognition (psychology); Noise reduction; Noise (video); Artificial intelligence; Geology; Seismology","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":[0.0008701577,0.0006827595,0.0005071145,0.0009313196,0.000222346,0.0006748784,0.0007351653,0.0006668675,0.001154128],"category_scores_gemma":[0.002432349,0.0003216907,0.0005782477,0.0006533689,0.0005098284,0.0006645917,0.0006093828,0.000731746,0.0007139579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003782627,"about_ca_system_score_gemma":0.0007232995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001314285,"about_ca_topic_score_gemma":0.001829584,"domain_scores_codex":[0.999478,0.00009607815,0.00003260949,0.0001019319,0.0002468083,0.00004462675],"domain_scores_gemma":[0.9989305,0.0003741795,0.0001574424,0.000181241,0.0003232771,0.00003335369],"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":[0.0002598392,0.0001022984,0.002434917,0.0002179269,0.00007170926,0.0001551196,0.00022299,0.1119213,0.3206654,0.01009619,0.001594703,0.5522577],"study_design_scores_gemma":[0.00001328651,0.00005607529,0.001860405,0.00001098219,0.00001102964,0.0001234601,0.00002183427,0.9120097,0.08193596,0.001813233,0.002114564,0.00002945591],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0146098,0.000040218,0.9845207,0.00003451437,0.00001003664,0.0000259533,0.00003292612,0.0004179504,0.0003077652],"genre_scores_gemma":[0.1295051,0.00006207997,0.869343,0.0000292308,0.00001407265,0.00007360594,0.0001354448,0.0001192916,0.0007181989],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001314285,"threshold_uncertainty_score":0.004601836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02293242908947079,"score_gpt":0.2217914504401385,"score_spread":0.1988590213506677,"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."}}