{"id":"W2138736858","doi":"10.1002/j.2161-4296.2003.tb00319.x","title":"A New Positioning Filter: Phase Smoothing in the Position Domain","year":2003,"lang":"en","type":"article","venue":"NAVIGATION Journal of the Institute of Navigation","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"NovAtel (Canada)","funders":"","keywords":"Kalman filter; Position (finance); Control theory (sociology); Smoothing; Filter (signal processing); Extended Kalman filter; Computer science; Phase (matter); Measure (data warehouse); Mathematics; Physics; Computer vision; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007035767,0.0001154108,0.000156515,0.0001435163,0.0001264033,0.0000550275,0.0003050363,0.0001045988,0.000007108938],"category_scores_gemma":[0.0001051643,0.00007971065,0.0001092466,0.0006531364,0.00006196362,0.0006891383,0.000009945938,0.0003721974,0.000001825237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001450383,"about_ca_system_score_gemma":0.00008048899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001267303,"about_ca_topic_score_gemma":0.000003461388,"domain_scores_codex":[0.9987109,0.0001049177,0.0006093592,0.00006888698,0.0003857353,0.0001202287],"domain_scores_gemma":[0.9992682,0.00004404738,0.0003367037,0.0001801352,0.0001436463,0.00002723233],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001333502,0.000266259,0.002028523,0.0002831336,0.0001461454,0.00007891277,0.0143223,0.6410318,0.16473,0.1223118,0.002419782,0.05224801],"study_design_scores_gemma":[0.009177053,0.0005027095,0.003473228,0.004536808,0.0002112056,0.002112786,0.003948508,0.01094336,0.7960714,0.1563415,0.01200007,0.0006813469],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8372785,0.0002350984,0.16,0.0006079812,0.0008671487,0.0001992628,0.00000434448,0.00003575043,0.0007719215],"genre_scores_gemma":[0.9926671,0.00001585062,0.007139897,0.00006378232,0.00007666032,0.000003060143,0.00001656116,0.00001095168,0.000006146294],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6313414,"threshold_uncertainty_score":0.3250506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009775922323270493,"score_gpt":0.2473652792258369,"score_spread":0.2375893569025664,"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."}}