{"id":"W4311528326","doi":"10.1177/15485129221141717","title":"Use of agent-based modeling to model intermediate force capabilities in (counter)mobility crowd scenarios","year":2022,"lang":"en","type":"article","venue":"The Journal of Defense Modeling and Simulation Applications Methodology Technology","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada; Carleton University","funders":"","keywords":"Computer science; Cellular automaton; Key (lock); Analytics; Range (aeronautics); Agency (philosophy); Representation (politics); Data science; Computer security; Engineering; Artificial intelligence","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":[0.002442886,0.000136388,0.0004083019,0.0008083007,0.0001729654,0.000009130396,0.0002961232,0.0001236941,0.000008561657],"category_scores_gemma":[0.0004236673,0.0001168424,0.00007629532,0.0006169849,0.0001352564,0.00009616203,0.00009130331,0.0005524899,2.995169e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001361344,"about_ca_system_score_gemma":0.00005854617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003284787,"about_ca_topic_score_gemma":0.00003282336,"domain_scores_codex":[0.9982667,0.0003703867,0.0008440148,0.0001612386,0.0001637392,0.0001939128],"domain_scores_gemma":[0.9983655,0.0007901855,0.000164856,0.0003991408,0.0002401076,0.00004023227],"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":[0.0001010486,0.00002903306,0.0003362058,0.00002818485,0.00002528948,2.873377e-7,0.0007905029,0.9907655,0.004466937,0.0003621602,0.000001298948,0.00309357],"study_design_scores_gemma":[0.0001940662,0.00006652624,0.00001283555,0.000009615324,0.00006276462,0.00001256733,0.001099872,0.9784122,0.0004428427,0.01957565,0.00001914234,0.00009198697],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4897882,0.000101302,0.5097466,0.0001588309,0.0000249738,0.0001488846,0.000006674856,0.00002278442,0.000001779888],"genre_scores_gemma":[0.9477034,0.0000315548,0.05209504,0.0000805405,0.00001289931,0.00005633814,0.000002381384,0.00001430193,0.000003543237],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4579152,"threshold_uncertainty_score":0.4764696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07690218819745608,"score_gpt":0.3197135634353977,"score_spread":0.2428113752379416,"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."}}