{"id":"W4379878902","doi":"10.2514/6.2023-3758","title":"Development of a Map-Matching Algorithm for the Analysis of Aircraft Ground Trajectories using ADS-B Data","year":2023,"lang":"en","type":"article","venue":"","topic":"Air Traffic Management and Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Trajectory; Matching (statistics); Process (computing); Algorithm; Graph; Map matching; Markov process; Line (geometry); Blossom algorithm; Line segment; Data mining; Artificial intelligence; Mathematics; Theoretical computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002753721,0.00007110851,0.0001517085,0.0001856256,0.00005920393,0.00001436625,0.0002141296,0.0000217658,0.00003286769],"category_scores_gemma":[0.000006348383,0.00005439861,0.0000427743,0.0007895838,0.00001266427,0.0001227759,0.00007445261,0.00002217976,7.903712e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001592848,"about_ca_system_score_gemma":0.00001182542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000295825,"about_ca_topic_score_gemma":0.0001740104,"domain_scores_codex":[0.9994213,0.000004525513,0.0002433845,0.0001003872,0.0001239221,0.0001064608],"domain_scores_gemma":[0.9995899,0.00009575111,0.00003722014,0.0002394834,0.00002685392,0.00001079422],"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":[0.000001532381,0.000006722961,0.00003702206,0.00009572797,0.001134137,1.306591e-7,0.00122603,0.9286928,0.0001013597,0.0001569738,0.000301582,0.06824601],"study_design_scores_gemma":[0.00008505974,0.000002035971,0.0009509167,0.00000918517,0.0004095249,2.550147e-8,0.001292965,0.9957166,0.0001939591,0.00001280022,0.001262445,0.0000644301],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02148277,0.00005451111,0.9779208,0.00001273209,0.0001204538,0.0001534401,0.00002885454,0.0001252929,0.0001011066],"genre_scores_gemma":[0.2518544,0.00005373212,0.7470623,0.000006385432,0.00004188275,0.00001506985,0.0006468031,0.00002618307,0.000293157],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2308585,"threshold_uncertainty_score":0.2218311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0517638008361735,"score_gpt":0.2770715497088638,"score_spread":0.2253077488726903,"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."}}