{"id":"W3046225151","doi":"","title":"Statistical analysis of extreme values for geomagnetic and geoelectric field variations for Canada","year":2016,"lang":"en","type":"article","venue":"EGU General Assembly Conference Abstracts","topic":"Earthquake Detection and Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Earth's magnetic field; Field (mathematics); Geology; Geophysics; Statistical analysis; Climatology; Meteorology; Geodesy; Geography; Statistics; Mathematics; Magnetic field; Physics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002021345,0.0001140345,0.000265419,0.0001723489,0.0001214376,0.00004479002,0.00009916085,0.00005660498,0.0009644648],"category_scores_gemma":[0.0003208829,0.00008116731,0.00008045603,0.0002968752,0.00002799904,0.00009502076,0.000004045377,0.0000368757,0.00000233883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005933946,"about_ca_system_score_gemma":0.0002594793,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1574358,"about_ca_topic_score_gemma":0.7199448,"domain_scores_codex":[0.9989578,0.00003327782,0.0003149226,0.0002564956,0.0001787594,0.0002587389],"domain_scores_gemma":[0.9983494,0.001079914,0.0001351802,0.0001244335,0.0001781701,0.0001329048],"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":[0.0001869452,0.00006661877,0.1864682,0.00007537116,0.001517138,0.000006786996,0.0001177587,0.007930197,0.0132688,0.004248012,0.00550601,0.7806082],"study_design_scores_gemma":[0.0002975028,0.0002553221,0.9369979,0.000006694226,0.0004825645,0.000001076177,0.00002019,0.05712996,0.002243177,0.001365628,0.001038872,0.000161137],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9092746,0.00008189477,0.08804941,0.001099929,0.0001059172,0.0001850025,0.0007449387,0.00001332296,0.000445015],"genre_scores_gemma":[0.994813,0.00003862659,0.00378365,0.0001550892,0.00006397873,0.000006496454,0.0001365786,0.000002464628,0.001000084],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7804471,"threshold_uncertainty_score":0.9999488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02277705272295678,"score_gpt":0.2333593092511916,"score_spread":0.2105822565282348,"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."}}