{"id":"W3131453904","doi":"","title":"HalentNet: Multimodal Trajectory Forecasting with Hallucinative Intents","year":2021,"lang":"en","type":"article","venue":"International Conference on Learning Representations","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Trajectory; Computer science; Discriminative model; Artificial intelligence; Machine learning; Motion (physics); Feature learning; Robot; Key (lock); Representation (politics)","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":[0.00006230555,0.0001316823,0.0001170808,0.0001238743,0.0001310157,0.00005022397,0.0001716081,0.00007585326,0.0006116701],"category_scores_gemma":[0.0001535799,0.0001327682,0.00004390974,0.0001412533,0.0001014839,0.0001616361,0.00003806061,0.0005059165,0.00007660239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009036379,"about_ca_system_score_gemma":0.0000550082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001732944,"about_ca_topic_score_gemma":0.0000750331,"domain_scores_codex":[0.9991512,0.00004271475,0.0001810696,0.0002514301,0.0002042997,0.0001692555],"domain_scores_gemma":[0.9993792,0.0001048018,0.00005261159,0.0001441276,0.0002750611,0.00004425812],"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":[0.0001573898,0.0003425514,0.08070753,0.0000464498,0.001092307,0.0006750054,0.006585112,0.7175558,0.01594254,0.0840201,0.0006501618,0.09222509],"study_design_scores_gemma":[0.0009125507,0.00009947155,0.05345136,0.0001523971,0.00002309674,0.0001198053,0.003089771,0.9289382,0.009838223,0.001428455,0.001611616,0.0003350818],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7321735,0.00005719678,0.03787368,0.001934619,0.0005359059,0.0001827871,0.00002598251,0.0009218747,0.2262944],"genre_scores_gemma":[0.9955649,0.00003896574,0.001737436,0.00003552356,0.00004474831,0.00004118136,0.00008832361,0.00002266452,0.002426238],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2633914,"threshold_uncertainty_score":0.6697359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04119373225655152,"score_gpt":0.2768955204699636,"score_spread":0.2357017882134121,"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."}}