{"id":"W1998098037","doi":"10.1504/ijcis.2014.062968","title":"Decision assistance agent in real-time simulation","year":2014,"lang":"en","type":"article","venue":"International Journal of Critical Infrastructures","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Reinforcement learning; Interdependence; Novelty; Computer science; Resource (disambiguation); Case-based reasoning; Computer security; Resource allocation; Multi-agent system; Operations research; Risk analysis (engineering); Engineering; Artificial intelligence; Business","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":[0.0002142368,0.00008359517,0.000130674,0.0001905802,0.00001321945,0.00006382515,0.000213809,0.00006259593,0.0002984427],"category_scores_gemma":[0.00078726,0.00007550422,0.00005859399,0.00006432363,0.00003921383,0.0002229498,0.000016052,0.0001708773,0.00001360028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001216216,"about_ca_system_score_gemma":0.00001450311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001584147,"about_ca_topic_score_gemma":0.000005846947,"domain_scores_codex":[0.9989303,0.00002963724,0.0004426164,0.00006249511,0.0004321719,0.0001028048],"domain_scores_gemma":[0.999035,0.0004846225,0.00004994245,0.00006471739,0.0002965731,0.00006913633],"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":[0.00005757229,0.00002193636,0.001125666,0.000008602047,0.00001995338,0.00002032572,0.0000906347,0.9588575,0.004124689,0.0114706,0.0005933353,0.02360918],"study_design_scores_gemma":[0.0005365831,0.00003664124,0.09642583,0.00008740697,0.000008183619,0.00003251957,0.00001637218,0.832745,0.0004713037,0.06767439,0.001851992,0.0001137755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6258121,0.00004649657,0.3670347,0.000308716,0.00170564,0.00003017914,0.000008027474,0.00003551104,0.005018623],"genre_scores_gemma":[0.9890702,0.00002160816,0.01048905,0.000115385,0.0002769441,5.001618e-7,0.000003173781,0.00001144669,0.00001170958],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3632581,"threshold_uncertainty_score":0.3267739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007636174746683488,"score_gpt":0.3121895345191768,"score_spread":0.3045533597724933,"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."}}