{"id":"W1895572989","doi":"10.1109/cig.2015.7317925","title":"Automatic mapping of human behavior data to personality model parameters for traffic simulations in virtual environments","year":2015,"lang":"en","type":"article","venue":"","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of New Brunswick","funders":"Bundesministerium für Bildung und Forschung","keywords":"Computer science; Baseline (sea); Human behavior; Implementation; Artificial intelligence; Virtual reality; Data modeling; Personality; Virtual actor; Simulation; Machine learning; Database","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":[0.0007614125,0.0006178162,0.000505078,0.001203617,0.0001987313,0.0006226611,0.0006676128,0.0004981245,0.0006628111],"category_scores_gemma":[0.005748129,0.0002912734,0.0003989295,0.0005308211,0.0001836077,0.0004810995,0.0006137821,0.0006403631,0.0003611549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003546216,"about_ca_system_score_gemma":0.0004259857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002883422,"about_ca_topic_score_gemma":0.003317914,"domain_scores_codex":[0.9994031,0.0002651342,0.0000316239,0.0001405886,0.0001214736,0.00003808301],"domain_scores_gemma":[0.9978577,0.0008416329,0.000371345,0.0005046127,0.0002897675,0.0001348139],"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":[0.0007350545,0.0007812,0.1019325,0.0001638982,0.0003536876,0.0002414626,0.000643422,0.4261034,0.04873332,0.001756658,0.002257759,0.4162976],"study_design_scores_gemma":[0.000008677085,0.00005189575,0.01106402,0.000006795339,0.000009243944,0.00004985676,0.00005678577,0.9834111,0.003836053,0.001178264,0.0003100878,0.0000171191],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3183812,0.00008060593,0.6765702,0.00007084452,0.00002774748,0.00009687741,0.0005709674,0.003475695,0.00072592],"genre_scores_gemma":[0.8810445,0.0000326859,0.1178004,0.0000158546,0.00000760583,0.00007793176,0.0006818628,0.00009075773,0.0002484952],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002883422,"threshold_uncertainty_score":0.005733311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1267955267859631,"score_gpt":0.3054239792683432,"score_spread":0.1786284524823802,"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."}}