{"id":"W2121629087","doi":"","title":"Pseudorange Multipath Mitigation By Means of Multipath Monitoring and De-Weighting","year":2001,"lang":"en","type":"article","venue":"","topic":"GNSS positioning and interference","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Pseudorange; Multipath propagation; Weighting; Multipath mitigation; Observable; Computer science; Outlier; Noise (video); Algorithm; Statistics; Mathematics; Global Positioning System; Telecommunications; Physics; Estimator; Artificial intelligence; Acoustics; 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":[0.0004955449,0.0005930196,0.0004016455,0.0006422697,0.0002118526,0.0004804071,0.0005784784,0.0003018628,0.0004449664],"category_scores_gemma":[0.001287438,0.0002274884,0.0003425742,0.0007367301,0.0003325684,0.000937864,0.0009493568,0.0004931443,0.0002280296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002022148,"about_ca_system_score_gemma":0.0004001979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004297108,"about_ca_topic_score_gemma":0.0009835365,"domain_scores_codex":[0.9995943,0.0000728412,0.00002876613,0.00007842904,0.0001854022,0.00004038895],"domain_scores_gemma":[0.9994683,0.000114829,0.0001317144,0.0001085301,0.0001604065,0.00001635241],"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":[0.0001997467,0.00009203314,0.004145313,0.0001878054,0.00007469123,0.0001371383,0.0002323459,0.05138788,0.2713054,0.01509423,0.0004720802,0.6566715],"study_design_scores_gemma":[0.00002697959,0.0005347615,0.008678468,0.0000434111,0.00008942456,0.00090522,0.0001239089,0.7480687,0.2190237,0.01099135,0.0114081,0.0001059713],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02928059,0.0001430507,0.9698142,0.00003638926,0.00001943976,0.00002164942,0.00001033209,0.0001827621,0.0004915931],"genre_scores_gemma":[0.3060703,0.000368135,0.6914099,0.00002856992,0.00005209685,0.0000519387,0.0000789014,0.00006413666,0.001876045],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0006422697,"threshold_uncertainty_score":0.002620697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008155604853714117,"score_gpt":0.2119275574907422,"score_spread":0.2037719526370281,"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."}}