{"id":"W2153751369","doi":"10.1109/fuzzy.2010.5584237","title":"Temporal fuzzy based modeling as applied to the class of man-machine interaction","year":2010,"lang":"en","type":"article","venue":"","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Robot; Automation; Artificial intelligence; Fuzzy logic; Machine learning; Robotics; Perception; Class (philosophy); Function (biology); Human–computer interaction; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001047165,0.0009592299,0.0006743827,0.001139728,0.0006370907,0.001694751,0.001648124,0.001110264,0.00345824],"category_scores_gemma":[0.002941453,0.0003372827,0.001347244,0.0010376,0.001270177,0.002057621,0.0006858491,0.001191976,0.000414458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002087646,"about_ca_system_score_gemma":0.00109917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01337819,"about_ca_topic_score_gemma":0.007292847,"domain_scores_codex":[0.9992868,0.0002031752,0.00004836042,0.0001557174,0.0002420051,0.00006386481],"domain_scores_gemma":[0.9988468,0.0006600698,0.0001725273,0.00007588496,0.0001770411,0.00006760816],"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":[0.00007631793,0.00008059573,0.001503295,0.0001461884,0.00008096722,0.0002554174,0.0003323048,0.64055,0.003570495,0.3284931,0.0007772055,0.02413412],"study_design_scores_gemma":[0.000006453039,0.00002520068,0.0002128839,0.00001021469,0.00001281133,0.00003294044,0.00002251359,0.9524555,0.0002423423,0.0461281,0.0008414151,0.000009675811],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01093508,0.0002698137,0.9832302,0.0002365474,0.00005740903,0.00004988715,0.0001015194,0.0001013396,0.005018293],"genre_scores_gemma":[0.7498873,0.001154915,0.2408949,0.0001580475,0.000155222,0.0004617395,0.0002535863,0.00004305878,0.006991398],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01337819,"threshold_uncertainty_score":0.02660066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02901553743720599,"score_gpt":0.3650176420481436,"score_spread":0.3360021046109377,"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."}}