{"id":"W2976336558","doi":"10.4236/pos.2019.103003","title":"Real-Time GPS/Galileo Precise Point Positioning Using NAVCAST Real-Time Corrections","year":2019,"lang":"en","type":"article","venue":"Positioning","topic":"GNSS positioning and interference","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Resources Canada; Government of Ontario","keywords":"Galileo (satellite navigation); Global Positioning System; Precise Point Positioning; Geodesy; Computer science; Real-time computing; Remote sensing; GNSS applications; Geography; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0005789287,0.0008663908,0.0006829167,0.00136623,0.0003383086,0.0009542756,0.001081188,0.0004650094,0.001626488],"category_scores_gemma":[0.00229941,0.0002673987,0.0005285973,0.002435764,0.0003385047,0.001020566,0.001046597,0.0008158595,0.001559493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006093723,"about_ca_system_score_gemma":0.001610955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06717665,"about_ca_topic_score_gemma":0.0783528,"domain_scores_codex":[0.9990944,0.00008407281,0.00004372227,0.0002145388,0.0004360182,0.0001272612],"domain_scores_gemma":[0.9991964,0.00004462702,0.00006759365,0.0002232807,0.0004287862,0.0000393929],"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":[0.001113195,0.0002705736,0.09811088,0.0006368242,0.000440535,0.0007736352,0.0006824663,0.2852409,0.03766473,0.003670411,0.04368631,0.5277095],"study_design_scores_gemma":[0.0003387485,0.0002606149,0.1129213,0.0001391357,0.0002106581,0.0003813368,0.0007155481,0.7944503,0.02890757,0.002405906,0.05908975,0.0001791269],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5800017,0.001526882,0.3226804,0.0007270948,0.00119422,0.0004032255,0.04035813,0.02676099,0.0263474],"genre_scores_gemma":[0.8494132,0.0005184246,0.09847946,0.0001131394,0.0001083005,0.000125536,0.04712432,0.0004415636,0.003676007],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06717665,"threshold_uncertainty_score":0.1335713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008518972456246728,"score_gpt":0.2246292300061677,"score_spread":0.2161102575499209,"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."}}