{"id":"W3132911058","doi":"10.1109/iros45743.2020.9340796","title":"Interacting Multiple Model Navigation System for Quadrotor Micro Aerial Vehicles Subject to Rotor Drag","year":2020,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Memorial University of Newfoundland","keywords":"Kalman filter; Control theory (sociology); Inertial navigation system; Navigation system; Rotor (electric); Drag; Filter (signal processing); Computer science; Extended Kalman filter; Control engineering; Engineering; Inertial frame of reference; Artificial intelligence; Aerospace engineering; Computer vision; Control (management)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0000648174,0.0001283874,0.0001544641,0.00003594756,0.00006307254,0.00007733054,0.00008229925,0.00006389336,0.00000448008],"category_scores_gemma":[0.00008202816,0.0001305747,0.00006075742,0.0001021967,0.000003851677,0.0001089955,0.00001530867,0.00006047995,0.00002814542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009529161,"about_ca_system_score_gemma":0.00001311204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003515317,"about_ca_topic_score_gemma":0.0000105408,"domain_scores_codex":[0.9992828,0.00001275247,0.0002610297,0.000174432,0.00009069297,0.0001782898],"domain_scores_gemma":[0.9996085,0.00008518693,0.00002869153,0.00009554325,0.00006821976,0.0001138958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005188306,0.000004229179,0.00005817247,0.0002234909,0.00001006066,7.200552e-7,0.0004196991,0.7268011,0.271606,0.0001483425,0.0004462547,0.0002300889],"study_design_scores_gemma":[0.0003650268,0.00003717801,0.000007294383,0.00006431634,0.000008002794,9.43246e-7,0.0002264265,0.8171155,0.1817568,0.000003473273,0.0002806835,0.00013432],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4019449,0.000005107478,0.5965768,0.00009278393,0.0002693984,0.0006876275,0.00002080866,0.0003078291,0.00009480688],"genre_scores_gemma":[0.9690381,3.803369e-7,0.03032078,0.00008545234,0.000319119,0.0001044036,0.00006037106,0.00004858914,0.00002285224],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5670931,"threshold_uncertainty_score":0.5324683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02290993507074155,"score_gpt":0.2318634156519619,"score_spread":0.2089534805812203,"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."}}