{"id":"W4312704766","doi":"10.1109/tits.2022.3219923","title":"FlightBERT: Binary Encoding Representation for Flight Trajectory Prediction","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":79,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Computer science; Binary number; Trajectory; Encoding (memory); Representation (politics); Block (permutation group theory); Algorithm; Artificial intelligence; Embedding; Entropy (arrow of time); Mathematics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002763095,0.0002512702,0.0002385384,0.0005722865,0.0004751343,0.00004858028,0.0001806582,0.00008946608,0.0001300601],"category_scores_gemma":[0.00000113745,0.0002956965,0.0002306662,0.0004789722,0.00002528148,0.0002800795,3.62114e-7,0.0002869217,0.00001619421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003208383,"about_ca_system_score_gemma":0.00002101113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003208743,"about_ca_topic_score_gemma":0.00002691123,"domain_scores_codex":[0.9981213,0.00007075987,0.0006992804,0.0003797008,0.0004584251,0.0002705189],"domain_scores_gemma":[0.9993891,0.00009066577,0.00008405943,0.0002755321,0.00006765562,0.00009295045],"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":[0.0001039789,0.0001442928,0.00002428734,0.0001682367,0.0001477646,0.000004552526,0.001317706,0.9741701,0.005252935,0.0005587146,0.01306238,0.005045049],"study_design_scores_gemma":[0.001323648,0.0007670413,0.0003635656,0.0001218545,0.0003067202,0.00001916061,0.00545932,0.7610906,0.075464,0.00004125159,0.1542838,0.0007590238],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01151081,0.0001500293,0.9729541,0.00004504552,0.00732214,0.001630263,0.0006282345,0.004920602,0.0008387858],"genre_scores_gemma":[0.9946589,0.0002377966,0.0003297867,0.00003544943,0.0001007839,0.003524459,0.0002837249,0.00007495665,0.0007541062],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9831482,"threshold_uncertainty_score":0.9999495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02647089200093828,"score_gpt":0.2441840478609866,"score_spread":0.2177131558600484,"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."}}