{"id":"W4307291243","doi":"10.1029/2022jb024401","title":"Spatiotemporal Graph Convolutional Networks for Earthquake Source Characterization","year":2022,"lang":"en","type":"article","venue":"Journal of Geophysical Research Solid Earth","topic":"Seismology and Earthquake Studies","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Los Alamos National Laboratory; National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Computer science; Graph; Earthquake location; Artificial neural network; Convolutional neural network; Seismology; Earthquake simulation; Warning system; Earthquake prediction; Data mining; Artificial intelligence; Geology; Theoretical computer science; Induced seismicity","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.002217062,0.0001266929,0.0003301965,0.0003179821,0.00114551,0.0001023908,0.0007637342,0.0000531636,0.00004510943],"category_scores_gemma":[0.0002848853,0.0001160374,0.0002452599,0.0007616322,0.0002265392,0.0004477118,0.0004434898,0.0009528134,0.00001448212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000363169,"about_ca_system_score_gemma":0.000299998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001747194,"about_ca_topic_score_gemma":0.000002435525,"domain_scores_codex":[0.9970591,0.0005650884,0.0004314803,0.0002585858,0.001096011,0.0005897258],"domain_scores_gemma":[0.9978033,0.0007123605,0.0002715467,0.0002505034,0.0007818264,0.0001804935],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.004193625,0.004230414,0.01584495,0.0001693758,0.001655338,0.0006764352,0.007238442,0.1042916,0.009492273,0.2320125,0.04660298,0.5735921],"study_design_scores_gemma":[0.002603836,0.005659084,0.5181271,0.00004103391,0.00002434269,0.0003142595,0.0002751953,0.3084978,0.0005110408,0.03579626,0.1276903,0.0004596568],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5009945,0.0001335564,0.494183,0.00365277,0.0006744876,0.0002454121,0.00001363201,0.00002534749,0.00007727149],"genre_scores_gemma":[0.9959276,0.0000358988,0.001736581,0.0003627033,0.0008305631,0.00003313387,0.00001764356,0.00001124099,0.001044599],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5731324,"threshold_uncertainty_score":0.881045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04140411651029358,"score_gpt":0.3191178947058325,"score_spread":0.2777137781955389,"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."}}