{"id":"W4226380192","doi":"10.48550/arxiv.2112.15252","title":"Modeling COVID-19 Transmission using IDSIM, an Epidemiological-Modelling Desktop App with Multi-Level Immunization Capabilities","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Herd immunity; Contact tracing; Epidemiology; Vaccination; Pandemic; Transmission (telecommunications); Booster (rocketry); Public health; Immunity; Environmental health; Medicine; Immunization; Coronavirus disease 2019 (COVID-19); Virology; Immunology; Infectious disease (medical specialty); Disease; Computer science; Immune system; Telecommunications; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0005864333,0.0007039926,0.0004591582,0.0003839027,0.000395244,0.0006791794,0.001000653,0.0007070696,0.007050387],"category_scores_gemma":[0.001424537,0.0003675738,0.000696296,0.000274298,0.0001985176,0.0004868131,0.000756106,0.0005759137,0.0007270385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000578785,"about_ca_system_score_gemma":0.001130811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02785194,"about_ca_topic_score_gemma":0.02304587,"domain_scores_codex":[0.9998624,0.00004654699,0.000009935502,0.0000285386,0.00002783288,0.00002472066],"domain_scores_gemma":[0.9993896,0.0004110555,0.00003650342,0.00003063697,0.00008577719,0.00004644473],"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":[0.0002948299,0.00017853,0.01657738,0.0002671075,0.0001060755,0.0003968683,0.000265584,0.9430686,0.002878566,0.005910938,0.008062273,0.02199338],"study_design_scores_gemma":[0.00003998831,0.00004172049,0.0008653108,0.00001419425,0.00002106281,0.00004527788,0.00003508389,0.9931346,0.0007112566,0.001183781,0.003895193,0.00001239289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5564758,0.0007672593,0.3602544,0.001289935,0.0004122457,0.0008356666,0.01572057,0.02258614,0.04165798],"genre_scores_gemma":[0.808144,0.000718596,0.1698653,0.0002509717,0.00007426476,0.0007812004,0.004558609,0.000798459,0.01480862],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02785194,"threshold_uncertainty_score":0.05537963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6904623875839632,"score_gpt":0.3615862600285099,"score_spread":0.3288761275554533,"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."}}