{"id":"W3175638899","doi":"10.1371/journal.pmed.1003682","title":"Sales of antibiotics and hydroxychloroquine in India during the COVID-19 epidemic: An interrupted time series analysis","year":2021,"lang":"en","type":"article","venue":"PLoS Medicine","topic":"Antibiotic Use and Resistance","field":"Immunology and Microbiology","cited_by":116,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto; McGill University","funders":"School of Medicine, University of California, San Francisco; School of Public Health, Imperial College London; University of California, San Francisco; Imperial College London","keywords":"Azithromycin; Medicine; Hydroxychloroquine; Antibiotics; Coronavirus disease 2019 (COVID-19); Interrupted time series; Interrupted Time Series Analysis; Pediatrics; Internal medicine; Disease; Infectious disease (medical specialty); Psychological intervention; Biology","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":[0.002200697,0.0003399466,0.0005403921,0.001582481,0.0002064569,0.001191215,0.0009082725,0.0005110145,0.001905636],"category_scores_gemma":[0.005265986,0.000295939,0.001210463,0.003515243,0.0004351024,0.0005015549,0.0005908224,0.001080983,0.0003873603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009477612,"about_ca_system_score_gemma":0.0006445902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02447654,"about_ca_topic_score_gemma":0.009806172,"domain_scores_codex":[0.9985921,0.0004392866,0.0001939518,0.0002718319,0.0002194478,0.0002834738],"domain_scores_gemma":[0.9930385,0.002397428,0.003290033,0.000451026,0.0005111194,0.0003119081],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004897623,0.0001122375,0.9892019,0.0001158717,0.0005132621,0.0003623001,0.0002848603,0.003907048,0.000187276,0.0003443451,0.0008545232,0.003626556],"study_design_scores_gemma":[0.00002148362,0.000222484,0.9758694,0.0000540495,0.0003325331,0.0004055634,0.0005786199,0.02098594,0.0001924774,0.0001610622,0.001147465,0.00002884834],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937779,0.000475101,0.0006861305,0.0001762746,0.00001823005,0.00002376853,0.004178017,0.00002644778,0.0006382309],"genre_scores_gemma":[0.9948617,0.0002955581,0.0003691286,0.00003711362,0.00002097421,0.00002562822,0.004111727,0.000007217255,0.0002709474],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02447654,"threshold_uncertainty_score":0.04866815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01728105120640651,"score_gpt":0.2711873061511775,"score_spread":0.253906254944771,"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."}}