{"id":"W3206935187","doi":"10.1029/2021sw002824","title":"Climatological Statistics of Extreme Geomagnetic Fluctuations With Periods From 1 s to 60 min","year":2021,"lang":"en","type":"article","venue":"Space Weather","topic":"Earthquake Detection and Analysis","field":"Earth and Planetary Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"British Antarctic Survey; Università degli Studi dell'Aquila; Sveriges Geologiska Undersökning; Sight Research UK; Florida Institute of Technology; Natural Environment Research Council; Alberta Agricultural Research Institute; U.S. Geological Survey; Universitetet i Tromsø","keywords":"Earth's magnetic field; Substorm; Geomagnetic latitude; Physics; Latitude; Magnetometer; Geophysics; Percentile; Interplanetary magnetic field; Atmospheric sciences; Solar wind; Geodesy; Geology; Magnetic field; Magnetosphere; Mathematics; Statistics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.00005160295,0.00008051128,0.0001543695,0.00004371557,0.00006284027,0.00003201752,0.00006230937,0.00003674591,0.03254478],"category_scores_gemma":[0.00005632695,0.00005935067,0.00003687109,0.0002898656,0.00005150387,0.00003121299,0.000006117331,0.00005942632,0.0003945625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001467253,"about_ca_system_score_gemma":0.00004015377,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001113376,"about_ca_topic_score_gemma":0.02096811,"domain_scores_codex":[0.9993159,0.0000592185,0.0001195548,0.0001882376,0.0001787753,0.0001383123],"domain_scores_gemma":[0.9995379,0.00009003201,0.0000380403,0.0001681564,0.00006942488,0.00009644552],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008445488,0.00008864998,0.9373215,0.00001533806,0.00013067,0.0002026443,0.001580815,0.00503506,0.004974916,0.0003866257,0.002087135,0.04809218],"study_design_scores_gemma":[0.0002153902,0.000202626,0.9796681,0.00001458489,0.00006440694,0.00001143395,0.001192686,0.005780247,0.0008097551,0.0003373361,0.01154993,0.0001534956],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9828921,0.0002814537,0.01137109,0.0008204381,0.00005375734,0.00005377872,0.0003507243,0.00002047468,0.004156177],"genre_scores_gemma":[0.9617472,0.00002071732,0.03401718,0.0001795004,0.00002827345,8.002544e-7,0.0001010287,0.000002959582,0.003902326],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04793868,"threshold_uncertainty_score":0.9968967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01625220417647126,"score_gpt":0.2094261148357846,"score_spread":0.1931739106593134,"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."}}