{"id":"W2526684554","doi":"","title":"A Case Study of Energetic Electron Precipitation Using Ground-Based VLF Radio Data","year":2014,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Ionosphere and magnetosphere dynamics","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Electron precipitation; Precipitation; Electron; Radio wave; Environmental science; Physics; Atmospheric sciences; Remote sensing; Meteorology; Geology; Magnetosphere; Nuclear physics; Plasma","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018657,0.000386652,0.0003917647,0.001099144,0.0007922431,0.001401297,0.0009956876,0.001917394,0.0009858457],"category_scores_gemma":[0.004541041,0.0002547559,0.0005304246,0.00250924,0.0005159156,0.001033975,0.0006071377,0.0004946999,0.0002290675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006033723,"about_ca_system_score_gemma":0.0004900262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02565686,"about_ca_topic_score_gemma":0.02803318,"domain_scores_codex":[0.9992169,0.0003119607,0.00005849138,0.0001177057,0.0001999477,0.00009489055],"domain_scores_gemma":[0.9966044,0.002219205,0.0002022064,0.0004485307,0.0003631746,0.0001624184],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001362587,0.001534421,0.379618,0.0007436876,0.0005905392,0.03694589,0.003515083,0.4402375,0.01995685,0.005028429,0.008442721,0.1020242],"study_design_scores_gemma":[0.0004949582,0.0009736908,0.2621742,0.000134201,0.0003707204,0.006171312,0.009064366,0.6758832,0.02022636,0.004867038,0.01947804,0.0001619353],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9850359,0.0002092011,0.008439961,0.0005074668,0.00003380179,0.0001155577,0.001820577,0.0002181972,0.003619441],"genre_scores_gemma":[0.9868886,0.0001284264,0.01111238,0.00003428453,0.00002634556,0.00002185943,0.0009194207,0.00003424838,0.0008343327],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02565686,"threshold_uncertainty_score":0.05101502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02220027352190259,"score_gpt":0.2641979451991808,"score_spread":0.2419976716772782,"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."}}