{"id":"W2733492159","doi":"","title":"Wide Area Navigation Algorithm for Marine DGPS Users under Disturbed Ionospheric Conditions","year":2004,"lang":"en","type":"article","venue":"Proceedings of the 17th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2004)","topic":"GNSS positioning and interference","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Differential GPS; TEC; Global Positioning System; Ionosphere; Remote sensing; Geodesy; Meteorology; Range (aeronautics); Latitude; Computer science; Storm; Environmental science; Geology; Geography; Telecommunications; Engineering; Geophysics","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":[],"consensus_categories":[],"category_scores_codex":[0.0004577547,0.0002290305,0.0003136695,0.00008232372,0.0001652984,0.00003193402,0.001273736,0.0001494093,0.000006565996],"category_scores_gemma":[0.0005680353,0.000151684,0.0004000381,0.0005286392,0.0004776989,0.000347688,0.0003366402,0.0003009333,0.000001069673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002237732,"about_ca_system_score_gemma":0.00004717157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007007804,"about_ca_topic_score_gemma":0.000002994764,"domain_scores_codex":[0.9978637,0.00001515298,0.0009841832,0.0002354796,0.0007219565,0.0001795766],"domain_scores_gemma":[0.9977052,0.0001483423,0.0009461152,0.0002842931,0.0008711896,0.00004488677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001097827,0.0005369424,0.007577026,0.0007458138,0.0003584096,1.837071e-7,0.0004138086,0.2183383,0.6871073,0.07506401,0.0006832648,0.009065186],"study_design_scores_gemma":[0.001031986,0.0001045926,0.03494073,0.005922063,0.0001245771,0.00001505465,0.0001129377,0.008019395,0.8812711,0.06771065,0.0004885549,0.0002583107],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9834707,0.00009028796,0.008236681,0.001687648,0.001817814,0.0007950159,0.0001504658,0.0001036619,0.003647676],"genre_scores_gemma":[0.9902872,0.0000375357,0.009385339,0.00004071851,0.00003958751,0.00003830059,0.00004881117,0.00002779864,0.00009472046],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2103189,"threshold_uncertainty_score":0.6185493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01259409763838496,"score_gpt":0.2464076910849471,"score_spread":0.2338135934465622,"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."}}