{"id":"W4378978290","doi":"10.1016/j.scs.2023.104661","title":"Generative design for COVID-19 and future pathogens using stochastic multi-agent simulation","year":2023,"lang":"en","type":"article","venue":"Sustainable Cities and Society","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Autodesk (Canada)","funders":"","keywords":"SAFER; Generative Design; Computer science; Workflow; Set (abstract data type); Transmission (telecommunications); Generative grammar; Machine learning; Artificial intelligence; Simulation; Mathematical optimization; Engineering; Mathematics; Computer security; Programming language; Operations management","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":[0.000161523,0.00009806732,0.00009353758,0.00002980765,0.000436512,0.00005580009,0.00002245832,0.00008821105,0.000003317781],"category_scores_gemma":[0.00002051991,0.00009922507,0.00003760468,0.0001332625,0.00003306129,0.0001037652,0.00002251792,0.00004575943,4.160888e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001126206,"about_ca_system_score_gemma":0.00004508471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001222413,"about_ca_topic_score_gemma":8.829336e-7,"domain_scores_codex":[0.999517,0.00001405914,0.00008393711,0.000120542,0.00004923518,0.0002152123],"domain_scores_gemma":[0.9997261,0.00008718027,0.00001697224,0.00005226313,0.00005393324,0.00006350471],"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":[0.00000438269,0.00000227586,0.000009278474,0.0002307757,0.00002746292,0.000001242697,0.004856626,0.9914709,0.00005458307,0.002638629,0.0004344972,0.0002693982],"study_design_scores_gemma":[0.0003239842,0.00001654076,0.00002849954,0.000003807961,0.00001939616,9.599494e-7,0.02472201,0.9718978,0.00002060596,0.001012799,0.001834537,0.0001190655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05861546,0.0005929416,0.9401815,0.00006474085,0.00008986447,0.0002587305,0.00001312897,0.0001794853,0.000004152631],"genre_scores_gemma":[0.9545461,0.0007377403,0.0428002,0.000271231,0.0003210757,0.0001038115,0.00007530807,0.00004888993,0.00109566],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8973813,"threshold_uncertainty_score":0.4046281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03589054838236782,"score_gpt":0.2719120963032117,"score_spread":0.2360215479208438,"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."}}