{"id":"W4378767837","doi":"10.1155/2023/8684886","title":"An Improved Adaptive Simulated Annealing Particle Swarm Optimization Algorithm for ARAIM Availability","year":2023,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"GNSS positioning and interference","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Civil Aviation Administration of China; Civil Aviation University of China; National Natural Science Foundation of China","keywords":"Particle swarm optimization; Simulated annealing; Computer science; Global Positioning System; Civil aviation; Algorithm; Reliability (semiconductor); Aviation; Real-time computing; Receiver autonomous integrity monitoring; ALARM; Engineering; Satellite navigation; Aerospace engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008881337,0.001010548,0.001135997,0.0007056464,0.0004979394,0.0009046256,0.001237203,0.001096229,0.001730894],"category_scores_gemma":[0.002494223,0.0005256873,0.000873473,0.0006551495,0.000498857,0.000785628,0.0008230237,0.0009867967,0.0002865469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000768917,"about_ca_system_score_gemma":0.001953464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01229726,"about_ca_topic_score_gemma":0.007065812,"domain_scores_codex":[0.9995185,0.0001320585,0.00003475437,0.0001100521,0.0001425494,0.00006208743],"domain_scores_gemma":[0.9993004,0.0003407123,0.00007449704,0.0000350869,0.0002192808,0.00003002275],"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":[0.00004447607,0.00002980989,0.0006851685,0.00004612737,0.00003583462,0.00002992548,0.00004033035,0.9633853,0.001105772,0.002231314,0.0007372972,0.03162871],"study_design_scores_gemma":[0.000007956719,0.00001175104,0.00006982885,0.000002460766,0.000004234334,0.000004132516,0.000003380777,0.9991892,0.0001300623,0.0003634548,0.000211147,0.000002358421],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01863856,0.00028008,0.977823,0.0001676089,0.00006894108,0.00006624911,0.00004313219,0.0003345881,0.00257797],"genre_scores_gemma":[0.5809004,0.0003572554,0.412718,0.000233408,0.00008204322,0.0005694556,0.0003712959,0.0001509256,0.004617062],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01229726,"threshold_uncertainty_score":0.02445138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01320614991966015,"score_gpt":0.2578620895574183,"score_spread":0.2446559396377581,"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."}}