{"id":"W3015774109","doi":"10.1101/2020.04.07.20057075","title":"A simple method to quantify country-specific effects of COVID-19 containment measures","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministero dell’Istruzione, dell’Università e della Ricerca; Dipartimenti di Eccellenza","keywords":"Social distance; Coronavirus disease 2019 (COVID-19); Pandemic; Psychological intervention; Promotion (chess); Politics; Development economics; Recreation; Geography; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Political science; Infectious disease (medical specialty); Disease; Economics; Medicine; Law","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":[0.006097658,0.0008831262,0.0008809118,0.002122366,0.0002644254,0.0008793045,0.0009348022,0.001011247,0.005512551],"category_scores_gemma":[0.01874942,0.0003328174,0.00191824,0.001716254,0.0006253938,0.001178622,0.001260044,0.00129118,0.0006321945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008100554,"about_ca_system_score_gemma":0.0006135803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006779543,"about_ca_topic_score_gemma":0.003681934,"domain_scores_codex":[0.997672,0.001339246,0.0001507608,0.0004072669,0.0002963515,0.0001342966],"domain_scores_gemma":[0.9843644,0.01127202,0.001705863,0.001596732,0.0008801156,0.0001808471],"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":[0.0002910863,0.0003069261,0.1354355,0.0006270105,0.001860591,0.0002457203,0.0001546346,0.7794091,0.003846667,0.01135889,0.003782309,0.06268165],"study_design_scores_gemma":[0.00009472331,0.001616102,0.1884108,0.0001830142,0.0005952767,0.0003139893,0.0005521733,0.7761352,0.006368855,0.01458981,0.01100553,0.0001345708],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5475774,0.001514529,0.4096733,0.0005355268,0.0003622338,0.00122221,0.02282868,0.001542161,0.01474389],"genre_scores_gemma":[0.9293734,0.0003075838,0.06271412,0.0001906532,0.00004919871,0.0008178644,0.004861204,0.0000976214,0.001588348],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.006779543,"threshold_uncertainty_score":0.0322479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3368799693794706,"score_gpt":0.4754276513433034,"score_spread":0.1385476819638329,"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."}}