{"id":"W4213433549","doi":"10.1109/wsc52266.2021.9715520","title":"Studying COVID-19 Spread Using a Geography Based Cellular Model","year":2021,"lang":"en","type":"article","venue":"2021 Winter Simulation Conference (WSC)","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Cellular automaton; Pandemic; Coronavirus disease 2019 (COVID-19); Infectious disease (medical specialty); Computer science; Epidemic model; Population; Public health; Geography; Disease; Operations research; Artificial intelligence; Mathematics; Environmental health; Medicine","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":[0.0003295355,0.0005325863,0.0005252335,0.0007673589,0.0005819788,0.001257458,0.0008417809,0.00152254,0.00279691],"category_scores_gemma":[0.001895676,0.0002883501,0.0007354421,0.0007539234,0.0006612552,0.0008339834,0.001132153,0.0007475277,0.0003016752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001610715,"about_ca_system_score_gemma":0.0008957483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04550203,"about_ca_topic_score_gemma":0.01837872,"domain_scores_codex":[0.9997432,0.00009905846,0.00001046956,0.00004904582,0.00003145867,0.00006681411],"domain_scores_gemma":[0.9992322,0.0004264585,0.0001236906,0.00004536732,0.00008972258,0.00008272335],"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":[0.00001486499,0.00001941769,0.001823515,0.00001273362,0.00001239924,0.0001087518,0.00005316955,0.9835254,0.0006035179,0.01228556,0.0003868239,0.001153883],"study_design_scores_gemma":[0.000004872093,0.00001221349,0.000352964,0.00000418833,0.000005003939,0.00001758741,0.00003870968,0.9968988,0.00006628451,0.002087349,0.0005070924,0.000004963687],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.750998,0.001600308,0.1951613,0.003271016,0.0002359392,0.0001226717,0.001251153,0.0002498039,0.04710998],"genre_scores_gemma":[0.982931,0.0005502157,0.009513659,0.0001102415,0.0000325196,0.00005744582,0.0002277345,0.00002557051,0.006551616],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04550203,"threshold_uncertainty_score":0.09047437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4928477452646918,"score_gpt":0.4613237216023788,"score_spread":0.03152402366231299,"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."}}