{"id":"W2968611636","doi":"10.3390/rs11161851","title":"Intelligent GPS L1 LOS/Multipath/NLOS Classifiers Based on Correlator-, RINEX- and NMEA-Level Measurements","year":2019,"lang":"en","type":"article","venue":"Remote Sensing","topic":"GNSS positioning and interference","field":"Engineering","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Hong Kong Polytechnic University","keywords":"Non-line-of-sight propagation; Computer science; Multipath propagation; Pseudorange; Artificial intelligence; Global Positioning System; Support vector machine; Pattern recognition (psychology); Telecommunications; GNSS applications","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":[0.000488819,0.0005257494,0.0004657393,0.0009748841,0.0002400393,0.0007341785,0.0004609158,0.0003617357,0.0007510651],"category_scores_gemma":[0.001260149,0.000167817,0.0002482521,0.0005033497,0.0001926679,0.000703265,0.0004674073,0.0003862874,0.0009821095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002858301,"about_ca_system_score_gemma":0.0003523516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001449037,"about_ca_topic_score_gemma":0.002045875,"domain_scores_codex":[0.9996209,0.00004987692,0.00002405108,0.0001134375,0.0001332285,0.00005845853],"domain_scores_gemma":[0.9994507,0.0001071019,0.00008558592,0.000061551,0.0002673181,0.00002766389],"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":[0.0003603364,0.000167347,0.044252,0.0001080758,0.00007409827,0.000140508,0.0001222283,0.06179154,0.05783032,0.001543772,0.002695998,0.8309138],"study_design_scores_gemma":[0.00002425005,0.000200612,0.02864989,0.00002301337,0.00006327008,0.0001083767,0.00009294399,0.932224,0.03492874,0.0006561325,0.002997319,0.00003145999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3371393,0.0002969961,0.6514856,0.0001191894,0.00008714914,0.0001233425,0.0002990133,0.003685059,0.006764458],"genre_scores_gemma":[0.8718744,0.0001507355,0.1225313,0.0001088435,0.00005652299,0.00008604601,0.0007577431,0.00008215267,0.004352218],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001449037,"threshold_uncertainty_score":0.002881229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04992607480052427,"score_gpt":0.2380082315872729,"score_spread":0.1880821567867486,"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."}}