{"id":"W3201917469","doi":"10.1109/iccv48922.2021.00753","title":"Where are you heading? Dynamic Trajectory Prediction with Expert Goal Examples","year":2021,"lang":"en","type":"article","venue":"2021 IEEE/CVF International Conference on Computer Vision (ICCV)","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Computer science; Inference; Trajectory; Machine learning; Artificial intelligence; Key (lock); Code (set theory)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000509566,0.0008612571,0.0006552659,0.0007016523,0.0003414405,0.0005610128,0.001316389,0.001259899,0.002834568],"category_scores_gemma":[0.002717749,0.0003286691,0.0004048323,0.0007733406,0.0003256006,0.001270215,0.0007489371,0.001219124,0.002196299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005585811,"about_ca_system_score_gemma":0.0007986104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0149983,"about_ca_topic_score_gemma":0.02859904,"domain_scores_codex":[0.9996852,0.00006216438,0.00001192962,0.0001598589,0.00004213973,0.00003877761],"domain_scores_gemma":[0.9991903,0.0003373526,0.00007608168,0.0001562508,0.0001671961,0.00007277267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001238036,0.0004356519,0.03133538,0.0002974775,0.000124157,0.000400525,0.0003326944,0.4104114,0.007081346,0.005372189,0.04688109,0.4960901],"study_design_scores_gemma":[0.00001349428,0.00003372582,0.002003629,0.00001489949,0.000008436264,0.0000488886,0.00005195818,0.9907363,0.002216302,0.003249696,0.001614068,0.000008616703],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2487655,0.0008200466,0.7232797,0.0009747035,0.0001495831,0.0001494996,0.006765886,0.01210203,0.006993139],"genre_scores_gemma":[0.7324728,0.0002376022,0.2521902,0.0001765747,0.00004574945,0.00008098707,0.0104236,0.0002162297,0.004156317],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0149983,"threshold_uncertainty_score":0.02982199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01459402291113371,"score_gpt":0.2471229547466728,"score_spread":0.2325289318355391,"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."}}