{"id":"W3009749694","doi":"10.1101/2020.03.02.974048","title":"Speed and strength of an epidemic intervention","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Human immunodeficiency virus (HIV); Intervention (counseling); Computer science; Scale (ratio); Basic reproduction number; Exponential function; Psychological intervention; Disease; Exponential growth; Mathematics; Medicine; Virology; Population; Environmental health; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006751897,0.0005427134,0.0008159586,0.001836413,0.0005881285,0.002766358,0.0011318,0.001942832,0.005637095],"category_scores_gemma":[0.04077083,0.0003981421,0.0006959073,0.0006074057,0.00299395,0.004885341,0.002293393,0.001949465,0.0005630417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001580211,"about_ca_system_score_gemma":0.0007281695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004753332,"about_ca_topic_score_gemma":0.0001707562,"domain_scores_codex":[0.9967715,0.001806819,0.0001503895,0.0005280159,0.0005178083,0.0002253907],"domain_scores_gemma":[0.9655929,0.02338042,0.005677916,0.001788475,0.002258769,0.001301548],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001591926,0.0001047179,0.007368848,0.0002703511,0.0001536184,0.000126704,0.0002621699,0.0650673,0.006587835,0.8939719,0.002816525,0.02311073],"study_design_scores_gemma":[0.00006300824,0.0003096483,0.00710852,0.0001562533,0.00008199264,0.0002844177,0.0002703776,0.2456007,0.002892892,0.736599,0.006560312,0.00007297515],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.403282,0.001812217,0.5117847,0.01265454,0.0005523643,0.0002292463,0.0004042521,0.0002763214,0.0690043],"genre_scores_gemma":[0.9715357,0.0006390216,0.02266366,0.0006609476,0.0002889206,0.0001121522,0.00007215248,0.00005330668,0.00397404],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006751897,"threshold_uncertainty_score":0.03570783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1292621916924713,"score_gpt":0.3544821904279004,"score_spread":0.2252199987354291,"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."}}