{"id":"W3124415190","doi":"10.1101/2021.01.15.21249884","title":"Estimating the effects of non-pharmaceutical interventions on the number of new infections with COVID-19 during the first epidemic wave","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"World Health Organization; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Coronavirus disease 2019 (COVID-19); Psychological intervention; Pandemic; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Epidemic control; 2019-20 coronavirus outbreak; Medicine; Environmental health; Demography; Geography; Virology; Outbreak; Infectious disease (medical specialty); Sociology; Nursing","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00277277,0.0004073385,0.0009264484,0.00004973036,0.0006179368,0.00003702375,0.0007000639,0.000190095,0.000244725],"category_scores_gemma":[0.06911607,0.0001730124,0.0007381953,0.0003665371,0.0005928317,0.00002825631,0.001678914,0.001529853,0.00000888632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002191182,"about_ca_system_score_gemma":0.0002035569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005930434,"about_ca_topic_score_gemma":0.0004884003,"domain_scores_codex":[0.9968482,0.0008638424,0.001023753,0.0004998632,0.0004044394,0.0003598874],"domain_scores_gemma":[0.9432475,0.05426575,0.0009617231,0.001258291,0.0001394162,0.0001273044],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001889782,0.001528821,0.8810572,0.04247236,0.004835747,0.00009622215,0.01373077,0.02633896,0.0003950371,0.02035804,0.008158981,0.0008389037],"study_design_scores_gemma":[0.00340307,0.0006024346,0.6789103,0.0276628,0.005380909,0.0002231928,0.001875402,0.03965524,0.005269669,0.2328906,0.0024257,0.001700721],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9210029,0.0003100015,0.05789507,0.01833276,0.0004551194,0.001590785,0.0000134416,0.00008278433,0.0003171334],"genre_scores_gemma":[0.9946157,0.0001159507,0.003230636,0.001194907,0.0001878022,0.000466749,0.000002724129,0.00003878053,0.0001467355],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2125326,"threshold_uncertainty_score":0.9387252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.248537371684428,"score_gpt":0.4697749457282309,"score_spread":0.2212375740438029,"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."}}