{"id":"W4404106079","doi":"10.2514/1.d0420","title":"Quantitative Assessment of Urban Air Collision Risks","year":2024,"lang":"en","type":"article","venue":"Journal of Air Transportation","topic":"Traffic and Road Safety","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Transport Canada","keywords":"Collision; Quantitative assessment; Environmental science; Risk assessment; Geography; Business; Risk analysis (engineering); Computer science; Computer security","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":[0.0002019992,0.00008051742,0.0001725252,0.0001413696,0.00001840985,0.000005259827,0.0000574504,0.00005418844,0.00001850484],"category_scores_gemma":[0.000002884972,0.0000653013,0.0001275845,0.0001892674,0.00001717864,0.0002355226,4.614744e-7,0.000193519,0.000002144787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004934187,"about_ca_system_score_gemma":0.00006546048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005952211,"about_ca_topic_score_gemma":0.00001782233,"domain_scores_codex":[0.9991596,0.00001413299,0.0004582634,0.00005516297,0.0002367704,0.00007605887],"domain_scores_gemma":[0.9996693,0.00006225993,0.00008324978,0.00004565052,0.00009724561,0.00004230072],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0000492671,0.00005055465,0.003967621,0.000341389,0.0001898836,0.00006263579,0.003193613,0.9783718,0.00396162,0.005383988,0.001756602,0.002671],"study_design_scores_gemma":[0.0005043217,0.0004343264,0.9301601,0.0005544291,0.0001652542,0.000009058775,0.0008295503,0.05932496,0.003431244,0.0001855135,0.004265577,0.0001356548],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8851395,0.001026337,0.1123569,0.0001072975,0.0007215225,0.00006281536,0.0000352272,0.00005230615,0.0004980974],"genre_scores_gemma":[0.9927464,0.0003170315,0.006816176,0.000005983865,0.00006256612,9.390418e-7,0.00001392571,0.00001596716,0.00002108565],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9261925,"threshold_uncertainty_score":0.266291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01897950110590594,"score_gpt":0.3020073426830858,"score_spread":0.2830278415771799,"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."}}