{"id":"W3176391915","doi":"10.2196/24630","title":"A Full-Scale Agent-Based Model to Hypothetically Explore the Impact of Lockdown, Social Distancing, and Vaccination During the COVID-19 Pandemic in Lombardy, Italy: Model Development","year":2021,"lang":"en","type":"article","venue":"JMIRx Med","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Dipartimento di Matematica e Informatica, Università degli Studi di Catania; Università degli Studi di Palermo","keywords":"Social distance; Pandemic; Herd immunity; Agent-based model; Outbreak; Computer science; Scale (ratio); Epidemic model; Test (biology); Coronavirus disease 2019 (COVID-19); Event (particle physics); Vaccination; Operations research; Geography; Simulation; Artificial intelligence; Engineering; Medicine; Virology; Environmental health; Population; Ecology; Cartography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004282593,0.0006783113,0.0007056638,0.0005016078,0.0006211459,0.0009116842,0.001715351,0.001784102,0.00466072],"category_scores_gemma":[0.001183057,0.0003808592,0.0009716289,0.0004250446,0.0006600249,0.0007798014,0.001040479,0.001012778,0.0004531306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001422486,"about_ca_system_score_gemma":0.001507256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04449319,"about_ca_topic_score_gemma":0.01948481,"domain_scores_codex":[0.9998393,0.00005796954,0.000006432943,0.00003625354,0.00001856107,0.00004137755],"domain_scores_gemma":[0.999495,0.0002743178,0.00006128896,0.00002503219,0.00008569629,0.00005872915],"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":[0.00002361546,0.00002556008,0.001250178,0.00001709787,0.00001312642,0.00006184409,0.00003147318,0.9962394,0.0001797302,0.001361117,0.0001767796,0.0006200804],"study_design_scores_gemma":[0.00002296669,0.00003045469,0.0004619433,0.000004650826,0.00001294755,0.00001221867,0.00002871195,0.9985464,0.0000394366,0.0005285516,0.0003056446,0.000006051555],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8063567,0.0005097577,0.1521121,0.001775605,0.0001428976,0.000459064,0.002401355,0.0004064899,0.03583593],"genre_scores_gemma":[0.975103,0.0002566965,0.01476084,0.0001076669,0.0000309245,0.0005005916,0.0005747012,0.00002461558,0.008640984],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04449319,"threshold_uncertainty_score":0.08846843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2826693243208166,"score_gpt":0.4361803315641993,"score_spread":0.1535110072433827,"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."}}