{"id":"W3037255891","doi":"10.1007/s42405-020-00280-9","title":"Bias-Compensated Pseudo-measurement Tracking Filter Design in Line-of-Sight Coordinates","year":2020,"lang":"en","type":"article","venue":"International Journal of Aeronautical and Space Sciences","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Nexen (Canada)","funders":"","keywords":"Line-of-sight; Filter (signal processing); Kalman filter; Noise (video); Tracking (education); Covariance; Control theory (sociology); Cartesian coordinate system; Observational error; Gaussian; System of measurement; Computer science; Mathematics; Physics; Computer vision; Artificial intelligence; Statistics","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":[0.001004796,0.001104948,0.0008513522,0.0004117527,0.0005526174,0.001202034,0.001090591,0.001515988,0.002251003],"category_scores_gemma":[0.003646931,0.000611257,0.0005208607,0.0007224604,0.000458463,0.001282033,0.0007633945,0.0009756544,0.001872629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005690039,"about_ca_system_score_gemma":0.001466877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003662515,"about_ca_topic_score_gemma":0.00360585,"domain_scores_codex":[0.9989364,0.0002500743,0.00006431276,0.0002663093,0.0003938432,0.00008912395],"domain_scores_gemma":[0.9986438,0.0003741051,0.0001329503,0.0001263019,0.0006914345,0.00003142],"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":[0.0007798651,0.0001425148,0.00203102,0.0006961005,0.000242802,0.000221292,0.0003210313,0.3154246,0.1062865,0.03107875,0.005494915,0.5372807],"study_design_scores_gemma":[0.00002986473,0.0001804012,0.0009761268,0.00003312383,0.00005018411,0.000199135,0.00001929958,0.9684761,0.0232482,0.002495353,0.004252462,0.00003967471],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00185405,0.0001391464,0.9972583,0.00004786211,0.00003943956,0.00001309646,0.0000192417,0.0001529928,0.0004758648],"genre_scores_gemma":[0.4123263,0.001252625,0.578321,0.0002984509,0.0001868382,0.0002839333,0.0004995498,0.0001785967,0.006652723],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003662515,"threshold_uncertainty_score":0.007530332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1311443516260364,"score_gpt":0.29564352258778,"score_spread":0.1644991709617437,"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."}}