{"id":"W4401536896","doi":"10.1109/access.2024.3443196","title":"Socially Intelligent Path-Planning for Autonomous Vehicles Using Type-2 Fuzzy Estimated Social Psychology Models","year":2024,"lang":"en","type":"article","venue":"IEEE Access","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Motion planning; Fuzzy logic; Path (computing); Fuzzy set; Artificial intelligence; Robot","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000422782,0.0002326023,0.0002890884,0.0002052642,0.000328138,0.0007814309,0.001359281,0.0001959542,0.000002885357],"category_scores_gemma":[0.00003885605,0.0002350558,0.0001064746,0.000581246,0.00007003728,0.0009703588,0.0001880091,0.0002485144,0.00003200101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001368319,"about_ca_system_score_gemma":0.0003975475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004239516,"about_ca_topic_score_gemma":6.491621e-7,"domain_scores_codex":[0.9981278,0.00006995363,0.0003705955,0.0006526164,0.0002401766,0.0005388582],"domain_scores_gemma":[0.999137,0.0001866136,0.0001072322,0.000296404,0.0001868361,0.00008592747],"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":[0.00005940305,0.0001767947,0.0003744986,0.0002875745,0.0003124975,0.0005398242,0.009614929,0.7156349,0.007088725,0.02818656,0.02629653,0.2114277],"study_design_scores_gemma":[0.000152775,0.0000530509,0.0002698417,0.0001061493,0.00002703241,0.00003258454,0.00001459125,0.9522864,0.0007032036,0.04573707,0.0003414344,0.0002758647],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02300694,0.0006049791,0.9693229,0.0005852004,0.004949276,0.0002757843,0.00001364152,0.000729367,0.0005119614],"genre_scores_gemma":[0.6951844,0.00001114623,0.3029378,0.000659722,0.001000648,0.00004267873,0.00001413374,0.00005955325,0.00008997325],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6721774,"threshold_uncertainty_score":0.9585298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2296767724842115,"score_gpt":0.4425430234530261,"score_spread":0.2128662509688146,"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."}}