{"id":"W3004441836","doi":"10.5880/fidgeo.2019.024","title":"BEAT - Bayesian Earthquake Analysis Tool","year":2019,"lang":"en","type":"article","venue":"Open MIND","topic":"Seismology and Earthquake Studies","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Bayesian probability; Geology; Computer science; Seismology; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003040899,0.000104154,0.0002472163,0.0001123891,0.0001247166,0.0002304293,0.001060064,0.00005567465,0.002773924],"category_scores_gemma":[0.00001645514,0.00009044017,0.00009678578,0.0006766437,0.00003457357,0.0004715564,0.0005536832,0.00008658188,0.004487699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007536319,"about_ca_system_score_gemma":0.00003745667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005185827,"about_ca_topic_score_gemma":0.00007495621,"domain_scores_codex":[0.998998,0.00005742791,0.0001543132,0.0004239781,0.0001274984,0.0002387484],"domain_scores_gemma":[0.9991397,0.00007144073,0.00005072424,0.0006586362,0.00003440243,0.00004515753],"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":[0.00002035028,0.00008521169,0.1749722,0.000003190745,0.0009965837,0.00005768035,0.002614983,0.0006695649,0.00009380522,0.003098488,0.001349993,0.816038],"study_design_scores_gemma":[0.0008617811,0.0002307379,0.6734541,0.00001268312,0.0002260788,0.00002154157,0.0002266717,0.01859917,0.001533831,0.001233846,0.3030058,0.000593691],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8743909,0.0000839184,0.05262849,0.001525665,0.0003130344,0.0002601619,0.000003912043,0.000006798677,0.07078714],"genre_scores_gemma":[0.9589626,0.000003062781,0.02886444,0.00031601,0.00002162357,0.000005067061,0.00000435115,0.000002977865,0.01181994],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8154442,"threshold_uncertainty_score":0.9981377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02013466666826937,"score_gpt":0.2702551721977596,"score_spread":0.2501205055294903,"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."}}