{"id":"W2011338681","doi":"10.1007/s11038-015-9463-0","title":"Detecting of ELF/VLF Signals Generated by GEMINIDS 2011 Meteors","year":2015,"lang":"en","type":"article","venue":"Earth Moon and Planets","topic":"Astro and Planetary Science","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Meteoroid; Fuze; Hertz; SIGNAL (programming language); Lightning (connector); Meteor shower; Mechanism (biology); Very low frequency; Meteor (satellite); Physics; Shower; Extremely low frequency; Acoustics; Frequency band; Range (aeronautics); Remote sensing; Computer science; Telecommunications; Geology; Engineering; Meteorology; Aerospace engineering; Astronomy; Geography; Electromagnetic field","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":[],"category_scores_codex":[0.0002278426,0.000112601,0.0001565262,0.00003222191,0.00005363024,0.00002377357,0.00008591927,0.00003228605,0.001004877],"category_scores_gemma":[0.000004167146,0.00009577587,0.00001887061,0.00006034633,0.00004035763,0.00009087,0.00001764313,0.00009644094,0.00009865421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001055846,"about_ca_system_score_gemma":0.00003022499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000731379,"about_ca_topic_score_gemma":0.00002007358,"domain_scores_codex":[0.9992846,0.00005026374,0.0001591659,0.000170288,0.0001401567,0.0001955481],"domain_scores_gemma":[0.9995583,0.00005979118,0.00008415087,0.0001009819,0.00002664689,0.0001701124],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001462774,0.0001062144,0.7260623,0.00002369639,0.0001521162,0.00001160015,0.001848896,0.00276514,0.08152722,0.0003124636,0.0554026,0.1316415],"study_design_scores_gemma":[0.005607935,0.002637585,0.2219441,0.0001112297,0.0001928045,0.00006091274,0.003368302,0.05902171,0.3727798,0.001027,0.3307745,0.002474076],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9876774,0.0001952966,0.0006840027,0.0000281537,0.000111556,0.00008511967,0.000221877,0.00001516827,0.01098145],"genre_scores_gemma":[0.9979131,0.000002710835,0.0006921306,0.00003694162,0.00008199004,0.000001147702,0.0002551141,0.00000458957,0.001012337],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5041181,"threshold_uncertainty_score":0.9999083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01796786816983912,"score_gpt":0.2093614303011244,"score_spread":0.1913935621312853,"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."}}