{"id":"W2256790706","doi":"10.1007/s40328-015-0153-1","title":"Comparative study of GPS-TEC smoothing techniques","year":2015,"lang":"en","type":"article","venue":"Acta Geodaetica et Geophysica","topic":"Ionosphere and magnetosphere dynamics","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"TEC; GNSS applications; Global Positioning System; Total electron content; Smoothing; Ionosphere; Remote sensing; Computer science; Space weather; Geodesy; Code (set theory); Environmental science; Meteorology; Geography; Geology; Telecommunications; Geophysics","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":[0.003053916,0.0005363743,0.0004499957,0.001700988,0.0004291876,0.001170847,0.0006744023,0.0006692006,0.002839704],"category_scores_gemma":[0.01136565,0.0002365978,0.0006703767,0.002099461,0.0001756916,0.001056487,0.000577566,0.000487779,0.0008771289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002676892,"about_ca_system_score_gemma":0.0008248514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005139428,"about_ca_topic_score_gemma":0.005883397,"domain_scores_codex":[0.9988785,0.0003924943,0.00008681376,0.0001512411,0.0003948752,0.00009608859],"domain_scores_gemma":[0.9916747,0.004837735,0.000338868,0.0007503138,0.002284704,0.0001138178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002633014,0.0001965432,0.0303569,0.0005480063,0.0004375068,0.0001469461,0.0005312982,0.05387196,0.02154978,0.003591231,0.002200592,0.8839362],"study_design_scores_gemma":[0.0002895499,0.0009488084,0.174886,0.0001812745,0.001121521,0.0007888845,0.0008445591,0.7418402,0.05643767,0.002870796,0.01959854,0.0001921835],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4442402,0.004957049,0.5351664,0.0003972668,0.0003709009,0.0001209971,0.001021729,0.003215348,0.01051015],"genre_scores_gemma":[0.8311194,0.001870588,0.1602391,0.00006874055,0.0001438379,0.00003861943,0.001671181,0.0005126477,0.00433583],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005139428,"threshold_uncertainty_score":0.01615083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02019346382475403,"score_gpt":0.2861599785347768,"score_spread":0.2659665147100228,"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."}}