{"id":"W4226097264","doi":"10.1111/poms.13726","title":"Pandemic lockdown, isolation, and exit policies based on machine learning predictions","year":2022,"lang":"en","type":"article","venue":"Production and Operations Management","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Agence Nationale de la Recherche","keywords":"Isolation (microbiology); Pandemic; Coronavirus disease 2019 (COVID-19); Computer science; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Business; Operations research; Operations management; Economics; Virology; Medicine; Engineering","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0006589316,0.0001102238,0.0001299211,0.0002261745,0.001622273,0.00004163419,0.00004865804,0.00001627725,0.0001680354],"category_scores_gemma":[0.0007348667,0.00009575499,0.00002301882,0.0003256658,0.00005618472,0.00006932261,0.0001751338,0.0001829471,0.000003310177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007730155,"about_ca_system_score_gemma":0.000006155627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007114607,"about_ca_topic_score_gemma":0.00009228971,"domain_scores_codex":[0.9989802,0.0001852136,0.0002237502,0.0003244471,0.000161625,0.0001247733],"domain_scores_gemma":[0.9995751,0.0001430191,0.00004681968,0.0001628601,0.00003768643,0.00003450735],"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":[0.00009812268,0.0006415344,0.1180069,0.0002595147,0.0001990285,0.000002432123,0.001891294,0.7003304,0.0001249208,0.1354213,0.03538259,0.007641975],"study_design_scores_gemma":[0.001052962,0.000699898,0.07803264,0.0000501649,0.0002618803,0.00001730789,0.00308202,0.6249736,0.00002524109,0.01948221,0.2717742,0.0005478251],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4429228,0.002255709,0.3070314,0.2174035,0.001776328,0.006858459,0.0001132356,0.002434262,0.01920435],"genre_scores_gemma":[0.9882481,0.0006549185,0.004048436,0.001097906,0.00009152787,0.0004422207,0.00002518604,0.00001161117,0.005380103],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5453253,"threshold_uncertainty_score":0.9996775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1276165337843003,"score_gpt":0.3657592505872012,"score_spread":0.2381427168029009,"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."}}