{"id":"W3180959986","doi":"10.3390/electronics10141626","title":"Managing SARS-CoV-2 Testing in Schools with an Artificial Intelligence Model and Application Developed by Simulation Data","year":2021,"lang":"en","type":"article","venue":"Electronics","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Response Biomedical (Canada); York University","funders":"Public Health Agency of Canada","keywords":"Operationalization; Computer science; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Data science; Coronavirus disease 2019 (COVID-19); Artificial intelligence; Management science; Knowledge management; Engineering; Medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001726591,0.000490133,0.0005100763,0.0007584777,0.0004471991,0.002371288,0.001244174,0.001506638,0.002345285],"category_scores_gemma":[0.005990293,0.0004190041,0.0005332665,0.0007374121,0.000746935,0.001807003,0.001217244,0.001312735,0.0002510283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001630717,"about_ca_system_score_gemma":0.001859287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01568092,"about_ca_topic_score_gemma":0.01144963,"domain_scores_codex":[0.9992186,0.0004778643,0.00004204313,0.000102683,0.00009117174,0.00006765139],"domain_scores_gemma":[0.997049,0.002124039,0.0002696709,0.0001559326,0.000285551,0.0001158951],"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":[0.00002496055,0.00003970131,0.002102024,0.00001739487,0.00001380035,0.0000542903,0.00006585022,0.9807895,0.0001305024,0.01216291,0.0003392831,0.00425983],"study_design_scores_gemma":[0.000006614358,0.00001581629,0.0002304141,0.000007279653,0.000004224357,0.000009146313,0.00003587589,0.9934791,0.00005881308,0.00554591,0.0006018205,0.000004962636],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2776057,0.0004207138,0.6831665,0.005482464,0.0001347041,0.000388239,0.0007762273,0.0005700456,0.03145546],"genre_scores_gemma":[0.9032345,0.0003467087,0.0917825,0.0001576878,0.00004506893,0.0002496575,0.0003065146,0.00004313339,0.003834179],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01568092,"threshold_uncertainty_score":0.03117925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3832322448358901,"score_gpt":0.4557288535258303,"score_spread":0.07249660868994023,"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."}}