{"id":"W2117220532","doi":"10.1109/plans.2012.6236837","title":"A weighted combining method for GPS antenna diversity","year":2012,"lang":"en","type":"article","venue":"","topic":"GNSS positioning and interference","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Multipath propagation; Pseudorange; Global Positioning System; Computer science; Antenna diversity; Fading; Diversity combining; GPS signals; Diversity gain; Standard deviation; Antenna (radio); Electronic engineering; Telecommunications; Algorithm; GNSS applications; Mathematics; Statistics; Assisted GPS; Engineering","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":[0.0009522113,0.0008399172,0.0005223388,0.001058347,0.0004048127,0.0008219312,0.0009237507,0.0006232701,0.002157245],"category_scores_gemma":[0.002497726,0.0003705282,0.0007597774,0.001433102,0.0004107379,0.001178605,0.001093674,0.0005704206,0.001107393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003891219,"about_ca_system_score_gemma":0.0004334546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007535765,"about_ca_topic_score_gemma":0.0009560766,"domain_scores_codex":[0.9987016,0.0002758997,0.00006083325,0.0002210861,0.0006812036,0.00005936672],"domain_scores_gemma":[0.999104,0.0002818517,0.00009154513,0.0001744861,0.0003208335,0.00002716676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002672278,0.00006219387,0.001165982,0.0001644616,0.0002312017,0.0001428256,0.0001841363,0.07231273,0.1410754,0.0132225,0.001228572,0.7699428],"study_design_scores_gemma":[0.00005544203,0.0006389959,0.002651952,0.0000429724,0.0002641208,0.001369457,0.00006879916,0.8693491,0.09348773,0.01112385,0.02078978,0.0001578433],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009736014,0.0002923806,0.9881422,0.00003088433,0.00003971454,0.00002969655,0.00002119034,0.0002509467,0.001456968],"genre_scores_gemma":[0.2460773,0.0005099256,0.7482242,0.00009604565,0.000126379,0.0001266377,0.0001306134,0.00009143989,0.004617494],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002157245,"threshold_uncertainty_score":0.007216692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02668323818895591,"score_gpt":0.2569280389986131,"score_spread":0.2302448008096571,"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."}}