{"id":"W3022805818","doi":"10.1101/2020.05.03.20089078","title":"The impact of long-term non-pharmaceutical interventions on COVID-19 epidemic dynamics and control","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Institute of General Medical Sciences; National Science Foundation","keywords":"Social distance; Psychological intervention; Coronavirus disease 2019 (COVID-19); Transmission (telecommunications); Epidemic control; Isolation (microbiology); Geography; Demography; Term (time); Basic reproduction number; Medicine; Sociology; Computer science; Population; Biology; Infectious disease (medical specialty); Disease","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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002977082,0.0005033249,0.001410267,0.00007949347,0.0002484745,0.00004345259,0.0007273478,0.000331981,0.0000914015],"category_scores_gemma":[0.0471397,0.0002944092,0.001180508,0.0001316528,0.0006035315,0.00002214175,0.001337335,0.001366992,0.00001637851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006281899,"about_ca_system_score_gemma":0.0001856327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001514951,"about_ca_topic_score_gemma":0.0001770304,"domain_scores_codex":[0.9965088,0.0007882525,0.001251769,0.000692291,0.0002907747,0.0004681469],"domain_scores_gemma":[0.9735519,0.02437628,0.000782094,0.000745661,0.0001008734,0.0004431911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004742945,0.000337147,0.9747183,0.003724524,0.001918455,0.0000760793,0.0002759826,0.0005583368,0.00009958456,0.01205152,0.003425191,0.002340619],"study_design_scores_gemma":[0.001732116,0.0005494523,0.7092205,0.0008354432,0.0008397793,0.00001360908,0.00004790206,0.05356,0.00003028497,0.2325292,0.00008196319,0.0005597125],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7742101,0.001690351,0.1938957,0.02692864,0.0003801113,0.002010067,0.000481568,0.0001855142,0.0002180008],"genre_scores_gemma":[0.9970114,0.001167646,0.0002970677,0.001102283,0.000129903,0.0001756217,0.00002037305,0.00004000622,0.00005575964],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2654977,"threshold_uncertainty_score":0.9999508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3622509099360582,"score_gpt":0.5353271738265316,"score_spread":0.1730762638904734,"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."}}