{"id":"W2903592362","doi":"10.1155/2018/7964641","title":"A SVM Approach of Aircraft Conflict Detection in Free Flight","year":2018,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Air Traffic Management and Optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Support vector machine; Computer science; Artificial intelligence; Probabilistic logic; Binary classification; False alarm; Classifier (UML); Constant false alarm rate; ALARM; Machine learning; Sigmoid function; Data mining; Pattern recognition (psychology); Probabilistic classification; Naive Bayes classifier; Engineering; Artificial neural network","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":[0.0007001918,0.0005419612,0.0006831107,0.0008015846,0.0003449446,0.0006892321,0.0007242665,0.0007158827,0.0008210095],"category_scores_gemma":[0.00160509,0.0002795327,0.0005575577,0.0006827762,0.0002729815,0.0008917489,0.000458055,0.0008951864,0.0002604508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003238052,"about_ca_system_score_gemma":0.000605561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002278131,"about_ca_topic_score_gemma":0.001530157,"domain_scores_codex":[0.9995112,0.000153954,0.00003219381,0.0001054645,0.0001482166,0.00004894497],"domain_scores_gemma":[0.9993955,0.0002497782,0.00006689139,0.00003712675,0.0002106288,0.00004008448],"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":[0.000236079,0.0001836307,0.005846432,0.0001869924,0.0001085231,0.0001807257,0.0001135749,0.5413088,0.01178022,0.01020662,0.00248994,0.4273585],"study_design_scores_gemma":[0.000001996479,0.00002428633,0.0004025927,0.000002826703,0.000003750764,0.00001993379,0.000006205693,0.9977959,0.000500808,0.0009887221,0.0002497345,0.000003279846],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02577822,0.000503113,0.9722951,0.0001089678,0.0000643294,0.00003053876,0.00004138489,0.0001806156,0.0009977077],"genre_scores_gemma":[0.7916279,0.0006278356,0.2041634,0.0001102816,0.0001840832,0.0001350102,0.000256152,0.00003593485,0.00285936],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002278131,"threshold_uncertainty_score":0.004529774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006312938247201381,"score_gpt":0.2037073814974249,"score_spread":0.1973944432502235,"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."}}