{"id":"W4247809187","doi":"10.32920/14639997","title":"Precise Point Positioning Using Triple GNSS Constellations in Various Modes","year":2021,"lang":"en","type":"preprint","venue":"","topic":"GNSS positioning and interference","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Galileo (satellite navigation); GNSS applications; Precise Point Positioning; Global Positioning System; Computer science; Constellation; Satellite; Orbit (dynamics); Satellite system; BeiDou Navigation Satellite System; Real-time computing; Quasi-Zenith Satellite System; Orbit determination; Satellite navigation; Remote sensing; Geodesy; Geography; Telecommunications; Engineering; Physics; Aerospace engineering","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":[0.0006129438,0.0007109722,0.0005232435,0.0007650572,0.0002652048,0.0009709361,0.000967993,0.0006568425,0.00106227],"category_scores_gemma":[0.001170249,0.0003486719,0.0006220212,0.001593063,0.0005676224,0.001442876,0.001245179,0.0006631296,0.000749969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006816393,"about_ca_system_score_gemma":0.0006825133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007544638,"about_ca_topic_score_gemma":0.006549952,"domain_scores_codex":[0.9991989,0.0001267429,0.00002863331,0.0002051619,0.0003704809,0.00007020144],"domain_scores_gemma":[0.9997262,0.00004423786,0.00004053011,0.00009561166,0.00007641058,0.00001704087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002055209,0.00003812243,0.01298278,0.000105488,0.00009388153,0.0002269626,0.0002321663,0.849864,0.01430211,0.01469617,0.001993745,0.1052591],"study_design_scores_gemma":[0.00002429616,0.0001285633,0.005603249,0.00002912033,0.00003413523,0.0002115836,0.00009011207,0.9730291,0.00631554,0.00712989,0.007355094,0.00004933385],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.109546,0.0003625425,0.8788894,0.0002168102,0.0001199914,0.00006346106,0.0008299386,0.001183993,0.008787862],"genre_scores_gemma":[0.8433001,0.0005719594,0.1489393,0.0001036632,0.00004754328,0.0001033144,0.001729138,0.0001457734,0.005059272],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007544638,"threshold_uncertainty_score":0.01500142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0261022509945208,"score_gpt":0.2492312902451742,"score_spread":0.2231290392506534,"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."}}