{"id":"W4285102511","doi":"10.1109/icra46639.2022.9811883","title":"Human Navigational Intent Inference with Probabilistic and Optimal Approaches","year":2022,"lang":"en","type":"article","venue":"2022 International Conference on Robotics and Automation (ICRA)","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Inference; Probabilistic logic; Bayesian inference; Bayesian probability; Artificial intelligence; Function (biology); Heading (navigation); Machine learning; Prior probability; Statistical model; Engineering","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":[0.000136898,0.000142904,0.0001261663,0.0001177984,0.0002604121,0.00006642975,0.0001672554,0.00004899727,0.0003045614],"category_scores_gemma":[0.00002046618,0.0001400189,0.00001731371,0.00008757212,0.0001221001,0.0001086392,0.0001255556,0.0003336196,0.000004127633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009389914,"about_ca_system_score_gemma":0.00003637379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004011866,"about_ca_topic_score_gemma":0.000006304231,"domain_scores_codex":[0.999163,0.00002557249,0.0002027689,0.000224164,0.0002551298,0.0001293115],"domain_scores_gemma":[0.9996679,0.00003331024,0.00006420862,0.000108223,0.00008321001,0.00004316334],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001174575,0.00005198628,0.001080459,0.00002111811,0.00005489008,0.000004226021,0.000261089,0.4140309,0.0002969984,0.5802847,0.00006889363,0.003833038],"study_design_scores_gemma":[0.0003511668,0.0001763331,0.01288549,0.0000258438,0.0000129961,0.00002457595,0.0004159375,0.9793204,0.00008104071,0.006268627,0.0002362721,0.0002013055],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9530544,0.00007898104,0.03008269,0.003627975,0.000416586,0.0004936387,0.0001211005,0.0006972739,0.01142735],"genre_scores_gemma":[0.9974203,0.00001527564,0.002009844,0.00006184595,0.00002453243,0.00009823903,0.0001302998,0.000014025,0.0002256761],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.574016,"threshold_uncertainty_score":0.5709803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03667728930411638,"score_gpt":0.2435174611707259,"score_spread":0.2068401718666095,"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."}}