{"id":"W2721697698","doi":"10.1002/2017sw001613","title":"Modeling geomagnetic induced currents in Australian power networks","year":2017,"lang":"en","type":"article","venue":"Space Weather","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Resources Canada; National Oceanic and Atmospheric Administration","keywords":"Earth's magnetic field; Geomagnetic storm; Storm; Latitude; Climatology; Meteorology; Transformer; Geology; Atmospheric sciences; Geodesy; Geography; Magnetic field; Physics; Engineering; Electrical engineering; Voltage","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":[0.0001837316,0.0001259265,0.000159654,0.0000410702,0.0001529036,0.0001052849,0.0003081706,0.00009181161,0.001373649],"category_scores_gemma":[0.0000895905,0.00009703962,0.00005240992,0.00009889925,0.00003277278,0.0001427542,0.00001784214,0.0002659709,0.0003270187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002718985,"about_ca_system_score_gemma":0.0000119589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005986556,"about_ca_topic_score_gemma":0.001387093,"domain_scores_codex":[0.9990224,0.00006339276,0.0001163087,0.0002431146,0.0001429411,0.0004118652],"domain_scores_gemma":[0.9994649,0.00004292683,0.00004072507,0.0003081834,0.00001515386,0.0001281648],"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":[0.00007212524,0.00009571928,0.3666569,0.000010326,0.0000174667,0.00004125196,0.0002468155,0.08905,0.0001586879,0.0002095478,0.0002638366,0.5431773],"study_design_scores_gemma":[0.0002423779,0.0001197981,0.6819603,0.00001907711,0.000004902482,0.000001050154,0.00002008325,0.3142935,0.0000176489,0.002516101,0.0006405356,0.0001645571],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896535,0.0001259988,0.0003577229,0.0009234542,0.0004570752,0.0001001009,0.000002630101,0.00001969008,0.008359785],"genre_scores_gemma":[0.9977577,0.00001209682,0.0005375048,0.00005102264,0.0001154996,0.000001043415,0.000003110256,0.000003740527,0.001518259],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5430127,"threshold_uncertainty_score":0.9995393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03367928542043957,"score_gpt":0.2798610549705166,"score_spread":0.246181769550077,"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."}}