{"id":"W4380563932","doi":"10.1117/12.2663898","title":"A machine learning-based state estimation approach for varying noise distributions","year":2023,"lang":"en","type":"article","venue":"","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Noise (video); Estimation; State (computer science); Artificial intelligence; Noise measurement; Machine learning; Noise reduction; Algorithm; 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":[0.0007019751,0.0005400219,0.0006576198,0.0004899459,0.0003451278,0.000635292,0.0009604073,0.0008842688,0.0009281412],"category_scores_gemma":[0.002193958,0.0003271346,0.0006407812,0.000649793,0.0005198831,0.0009814771,0.0006750327,0.0009193333,0.0003816379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005567996,"about_ca_system_score_gemma":0.0006297277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002917273,"about_ca_topic_score_gemma":0.003047971,"domain_scores_codex":[0.9995283,0.000115822,0.00002852488,0.0001478156,0.0001461575,0.00003343013],"domain_scores_gemma":[0.9994431,0.0002982076,0.00008421893,0.00007292122,0.00009108496,0.00001034596],"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":[0.00003801507,0.00004026073,0.0004555522,0.00006806258,0.00004929057,0.00007171066,0.00009232003,0.8562778,0.006281579,0.02281793,0.000468973,0.1133385],"study_design_scores_gemma":[0.000001038355,0.00001137896,0.00006322966,0.000002989569,0.000003966852,0.00001682514,0.000002215694,0.996769,0.0007543645,0.001999734,0.0003709102,0.000004322187],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001742395,0.00006426441,0.9976599,0.00003362899,0.00001166662,0.000006651543,0.000006180268,0.00008797316,0.0003872503],"genre_scores_gemma":[0.6270834,0.000482423,0.366111,0.0001734612,0.0001068864,0.0001521858,0.0001362027,0.00008869618,0.005665782],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002917273,"threshold_uncertainty_score":0.005800605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02523548552279278,"score_gpt":0.2618103159786239,"score_spread":0.2365748304558311,"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."}}