{"id":"W3049586136","doi":"","title":"Probing disturbances over canadian ionosphere using advance data analysis of wave decomposition","year":2016,"lang":"en","type":"article","venue":"41st COSPAR Scientific Assembly","topic":"Earthquake Detection and Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Ionosphere; Decomposition; Remote sensing; Environmental science; Econometrics; Meteorology; Computer science; Climatology; Geology; Geophysics; Mathematics; Geography; Chemistry","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":[0.0006644688,0.0001428094,0.0002878695,0.000436791,0.0004797411,0.000205616,0.0004452679,0.00005721987,0.002333948],"category_scores_gemma":[0.0000648137,0.0001019757,0.0001271753,0.002337141,0.0001793624,0.0007980697,0.00002901808,0.00006053769,0.00007735087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002692101,"about_ca_system_score_gemma":0.0001914269,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.04498541,"about_ca_topic_score_gemma":0.6976522,"domain_scores_codex":[0.9981217,0.00008730577,0.000339274,0.0006680812,0.0004080098,0.0003756],"domain_scores_gemma":[0.9985099,0.00009881161,0.0002226545,0.0007949311,0.0001240504,0.0002496591],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003661826,0.00004716658,0.7833073,0.00002520825,0.0008434593,0.00002487144,0.0001969827,0.01653328,0.01306086,0.0001288366,0.001750436,0.184045],"study_design_scores_gemma":[0.0002171795,0.00002901978,0.4877329,0.00007329261,0.000607093,0.00000416855,0.0001523259,0.4977665,0.001654918,0.00007924445,0.01136192,0.0003214459],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.987839,0.0003749442,0.008490176,0.0001278506,0.0005998844,0.0001072286,0.000965473,0.00002946708,0.001465954],"genre_scores_gemma":[0.9969785,0.00001809158,0.001714103,0.00003737576,0.00004081285,4.346347e-7,0.0004546949,0.00000364459,0.0007522972],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6526668,"threshold_uncertainty_score":0.9985781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04742007392441369,"score_gpt":0.266073097940052,"score_spread":0.2186530240156383,"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."}}