{"id":"W6980178528","doi":"","title":"Bayesian estimation of non-linear centroid moment tensors using multiple seismic data sets","year":2023,"lang":"","type":"article","venue":"Publication Database GFZ (GFZ German Research Centre for Geosciences)","topic":"Categorization, perception, and language","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Centroid; Waveform; Bayesian probability; Amplitude; Moment (physics); Covariance; Inversion (geology); A priori and a posteriori; Inverse theory; Covariance matrix","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":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01038229,0.0005514164,0.0006257946,0.002717934,0.001795635,0.0005497594,0.00331491,0.0003277942,0.002725488],"category_scores_gemma":[0.003739579,0.0005779428,0.0001888292,0.007389044,0.001199487,0.002625342,0.001518408,0.0006268536,0.0007366209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005018556,"about_ca_system_score_gemma":0.001488338,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006622804,"about_ca_topic_score_gemma":0.0009081655,"domain_scores_codex":[0.9893339,0.001054721,0.001752513,0.002596655,0.002797648,0.002464602],"domain_scores_gemma":[0.9904136,0.001142965,0.000873678,0.004449732,0.002252535,0.0008674989],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001190401,0.005951276,0.02977387,0.003585985,0.0005114491,0.00004416239,0.04042735,0.03482737,0.01344271,0.005782388,0.7117022,0.1527608],"study_design_scores_gemma":[0.001903309,0.0001096457,0.009442711,0.0001280275,0.00007725089,0.00001396781,0.004246284,0.879764,0.0002917727,0.0001396201,0.1034099,0.0004734428],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4708001,0.0003948845,0.4061929,0.01332583,0.002791409,0.00979788,0.09578038,0.0004374606,0.0004792082],"genre_scores_gemma":[0.833508,0.0006384219,0.007419162,0.0001910946,0.0006623534,0.0002245093,0.1525345,0.0001224414,0.004699629],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8449367,"threshold_uncertainty_score":0.9999922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.104267881092609,"score_gpt":0.4292640799638276,"score_spread":0.3249961988712187,"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."}}