{"id":"W2104283176","doi":"10.1098/rspb.2010.1469","title":"Optimal antiviral treatment strategies and the effects of resistance","year":2010,"lang":"en","type":"article","venue":"Proceedings of the Royal Society B Biological Sciences","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Outbreak; Antiviral treatment; Optimal control; Attack rate; Resistance (ecology); Coronavirus disease 2019 (COVID-19); Mathematical optimization; Computer science; Mathematics; Medicine; Virology; Biology; Virus; Infectious disease (medical specialty); Ecology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00238342,0.0007591401,0.000813284,0.0007565778,0.000469065,0.001581237,0.0007881896,0.001813938,0.003563291],"category_scores_gemma":[0.01730411,0.0004798241,0.0005536609,0.0003524561,0.001806812,0.00200514,0.0007928341,0.001071249,0.000221739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00202399,"about_ca_system_score_gemma":0.001612203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002120289,"about_ca_topic_score_gemma":0.001212419,"domain_scores_codex":[0.9983951,0.000840611,0.00007284518,0.0001935264,0.0001688713,0.0003289873],"domain_scores_gemma":[0.9934366,0.004526514,0.001362389,0.0001780078,0.0002627069,0.0002339295],"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":[0.000381384,0.0002986105,0.003272729,0.000286446,0.0001043223,0.0002961596,0.0001539516,0.7741567,0.006526772,0.185289,0.001965874,0.02726808],"study_design_scores_gemma":[0.0002302692,0.0004968643,0.003542058,0.0001273939,0.0001022804,0.0001907892,0.0003568574,0.7715512,0.002948315,0.2176199,0.002778343,0.00005568946],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6318131,0.007778058,0.2941883,0.01168311,0.0002378734,0.0002385379,0.000414014,0.0002084817,0.05343851],"genre_scores_gemma":[0.9862904,0.001272272,0.01043759,0.000305754,0.00004421251,0.00005006815,0.00002831903,0.00001577932,0.001555679],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003563291,"threshold_uncertainty_score":0.01468515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07737205307636942,"score_gpt":0.3526599234308695,"score_spread":0.2752878703545001,"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."}}