{"id":"W4409336685","doi":"10.1145/3729226","title":"TrajLearn: Trajectory Prediction Learning using Deep Generative Models","year":2025,"lang":"en","type":"article","venue":"ACM Transactions on Spatial Algorithms and Systems","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Generative grammar; Trajectory; Computer science; Artificial intelligence; Deep learning; Machine learning; Physics","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":[0.0001466448,0.0001893329,0.0002106916,0.0002878324,0.0002779116,0.00009001313,0.0001000233,0.0001357955,0.000007864746],"category_scores_gemma":[0.000003858339,0.0001933639,0.00006549993,0.0002054734,0.00003375399,0.0002221481,0.000004280431,0.0003051056,0.000001907204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001027243,"about_ca_system_score_gemma":0.00001387431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002774868,"about_ca_topic_score_gemma":0.00005314554,"domain_scores_codex":[0.9990582,0.000064216,0.0002870248,0.0002423998,0.0001581144,0.0001900436],"domain_scores_gemma":[0.9996412,0.00003698329,0.00002769961,0.0001931738,0.00003891231,0.00006202977],"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":[0.000009744931,0.00002725303,0.0000128793,0.00006657839,0.0001144786,0.000001765686,0.000296622,0.8529226,0.0006007569,0.000181935,0.0001176533,0.1456477],"study_design_scores_gemma":[0.0003718189,0.00007590131,0.0001373645,0.00008407074,0.00006455336,0.000006353207,0.0004992835,0.9962421,0.0004855747,0.00007044958,0.001815717,0.0001468211],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005348297,0.0004639432,0.9887125,0.00002774695,0.001273892,0.0003730776,0.00002246929,0.00237284,0.001405263],"genre_scores_gemma":[0.994545,0.0005101461,0.004398794,0.00002238168,0.0001021507,0.00009840463,0.000009286347,0.00002621655,0.0002876141],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9891967,"threshold_uncertainty_score":0.7885152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02028853318708677,"score_gpt":0.2337149944559781,"score_spread":0.2134264612688913,"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."}}