{"id":"W3092298165","doi":"10.1186/s12992-020-00623-x","title":"Lessons learned from COVID-19 for the post-antibiotic future","year":2020,"lang":"en","type":"article","venue":"Globalization and Health","topic":"Antibiotic Use and Resistance","field":"Immunology and Microbiology","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Global Health Research; Global Affairs Canada; McMaster University; York University; University of Ottawa","funders":"","keywords":"Scarcity; Global health; Health care; Social policy; Economic growth; Pandemic; Development economics; Political science; Public relations; Coronavirus disease 2019 (COVID-19); Business; Economics; Medicine; Infectious disease (medical specialty)","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":[],"consensus_categories":[],"category_scores_codex":[0.0001281853,0.00008573987,0.0001563478,0.00001106133,0.0005296236,0.00001909669,0.000100356,0.000113496,0.0001397873],"category_scores_gemma":[0.00008180253,0.0000569517,0.00003725899,0.00009582276,0.00008365826,0.00002479697,0.00002650985,0.00008189729,0.00004870639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002587806,"about_ca_system_score_gemma":0.0002314946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005492522,"about_ca_topic_score_gemma":0.0004016131,"domain_scores_codex":[0.999343,0.00007728983,0.0001544445,0.0002198138,0.00002205991,0.0001833496],"domain_scores_gemma":[0.9996222,0.00006775928,0.00009246869,0.0001064836,0.00003660072,0.00007448419],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008930576,0.000158574,0.01807081,0.0007623436,0.0004384276,0.000003581696,0.01029645,0.00009106888,0.005212111,0.2887983,0.6045874,0.07068785],"study_design_scores_gemma":[0.001449585,0.0001759421,0.02073678,0.00002112953,0.00004105804,0.000004739027,0.002979438,0.0001272893,0.0001877938,0.0005509515,0.9736054,0.0001199116],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.004667195,0.03337427,0.05287765,0.9068281,0.0007157829,0.0006160614,0.0005633128,0.0001204788,0.0002371454],"genre_scores_gemma":[0.8783326,0.007951441,0.0001761733,0.1122811,0.000204902,0.000001761185,0.000637527,0.00001068022,0.0004038177],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.8736654,"threshold_uncertainty_score":0.4073491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07824643351191446,"score_gpt":0.3527061391291158,"score_spread":0.2744597056172013,"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."}}