{"id":"W6920290296","doi":"10.60692/vp33g-emv26","title":"Accelerating the integration of the metaverse into urban transportation using fuzzy trigonometric based decision making","year":2024,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Fuzzy logic; Possible world; Consistency (knowledge bases); Rank (graph theory); Metaverse; Trigonometry; Universe","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":[0.0004469918,0.0001328319,0.0001306135,0.0003869612,0.0001436986,0.0002370708,0.0001564399,0.00007540478,0.00001388797],"category_scores_gemma":[0.00002706829,0.00007878341,0.0001165481,0.00108177,0.00001697636,0.0007027016,0.000007405582,0.0001254484,0.00002971753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001977347,"about_ca_system_score_gemma":0.00003641635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000598981,"about_ca_topic_score_gemma":0.000002424634,"domain_scores_codex":[0.9988287,0.00004035127,0.000646521,0.00007771384,0.0002997941,0.0001069076],"domain_scores_gemma":[0.9994677,0.00003976254,0.0001326089,0.0002366273,0.0001033002,0.00002000528],"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":[0.00003493935,0.000001906142,0.01448155,0.001315311,0.0001007569,8.675572e-7,0.1251363,0.8355786,0.0002092003,0.003355399,0.00007225143,0.0197129],"study_design_scores_gemma":[0.0001787921,0.000005780721,0.01610079,0.0004436029,0.00005604299,0.000002316727,0.006068389,0.9760197,0.0009673421,0.00000748951,0.0000558629,0.00009391816],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5750806,0.00001327475,0.4235043,0.000008797479,0.0005220068,0.0002306752,0.00002573492,0.0001462197,0.0004684282],"genre_scores_gemma":[0.9971892,1.611633e-7,0.002685559,0.00002975166,0.00003871639,0.00002017913,0.00001692327,0.00001389623,0.000005605614],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4221087,"threshold_uncertainty_score":0.3212694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04187715885939555,"score_gpt":0.2388670193647453,"score_spread":0.1969898605053498,"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."}}