{"id":"W3087139160","doi":"10.30577/jba.v3i2.60","title":"Lockdown Policy Dilemma: COVID-19 Pandemic versus Economy and Mental Health","year":2020,"lang":"en","type":"article","venue":"Journal of Biomedical Analytics","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pandemic; Mental health; Dilemma; Coronavirus disease 2019 (COVID-19); Quarter (Canadian coin); Recreation; Economic cost; Development economics; Economics; Economic impact analysis; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Business; Economic growth; Geography; Medicine; Political science; Psychiatry; Disease; Infectious disease (medical specialty)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001073407,0.0001855933,0.0007488723,0.0005011984,0.0001224339,0.00006365476,0.000294397,0.0001418513,0.0003167838],"category_scores_gemma":[0.002547394,0.000179116,0.0001898614,0.0005602798,0.0002406096,0.0002246602,0.0001318072,0.0004350854,0.00006905864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001020817,"about_ca_system_score_gemma":0.001056905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002255073,"about_ca_topic_score_gemma":0.00001784958,"domain_scores_codex":[0.9978517,0.0000333304,0.001318289,0.0002709936,0.0001179273,0.0004077738],"domain_scores_gemma":[0.9964992,0.000253106,0.001106293,0.0001465176,0.0000373422,0.001957472],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002348492,0.0009077415,0.4582817,0.001446439,0.002487552,0.000314845,0.01311924,0.0005789144,0.0001193804,0.083467,0.4121765,0.02475221],"study_design_scores_gemma":[0.004686739,0.001023102,0.002224085,0.00001991215,0.00001937637,0.0001298213,0.0002268928,0.005517941,0.000001637588,0.005086379,0.9808304,0.0002337156],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2079095,0.008140766,0.04898657,0.7306627,0.001477684,0.0004254379,0.000674892,0.00008203345,0.00164044],"genre_scores_gemma":[0.9624251,0.002140996,0.0005541536,0.03354714,0.001232001,7.44873e-7,0.00001528182,0.00002155275,0.00006306813],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7545156,"threshold_uncertainty_score":0.7304139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1049946004493742,"score_gpt":0.3372665033660161,"score_spread":0.2322719029166419,"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."}}