{"id":"W3187062000","doi":"10.1093/jac/dkab180","title":"Analysing the trend over time of antibiotic consumption in the community: a tutorial on the detection of common change-points","year":2021,"lang":"en","type":"article","venue":"Journal of Antimicrobial Chemotherapy","topic":"Antibiotic Use and Resistance","field":"Immunology and Microbiology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universiteit Antwerpen; Fonds Wetenschappelijk Onderzoek; European Centre for Disease Prevention and Control; GlaxoSmithKline; Vlaamse regering; Pfizer","keywords":"Consumption (sociology); Quarter (Canadian coin); Index (typography); Set (abstract data type); Data set; Computer science; Econometrics; Operations research; Statistics; Geography; Mathematics; Artificial intelligence; Social science; Sociology","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":[],"consensus_categories":[],"category_scores_codex":[0.001201525,0.000126171,0.0003885271,0.0001021789,0.0001997611,0.0000182607,0.0003465673,0.0001459886,0.00009686358],"category_scores_gemma":[0.00005248402,0.00006245293,0.0002304005,0.0002883763,0.0003425941,0.00006283187,0.00002547313,0.0006562038,0.000006282779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000278006,"about_ca_system_score_gemma":0.00003781772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009506949,"about_ca_topic_score_gemma":0.0002213795,"domain_scores_codex":[0.9980236,0.001154768,0.0005112218,0.00007820973,0.00008261492,0.0001495391],"domain_scores_gemma":[0.9983574,0.0005693363,0.0006659724,0.0003179474,0.00008256322,0.000006760582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006597693,0.0004802851,0.001877181,0.00003123787,0.000271271,0.000005668852,0.003464052,0.000004421473,0.9908462,0.00004958482,0.0007170133,0.001593287],"study_design_scores_gemma":[0.00180705,0.0002636893,0.03126221,0.0004203691,0.0001084548,0.0001622856,0.0006555796,0.000009079974,0.9639742,0.00005280738,0.001203618,0.00008067287],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965822,0.0006308442,0.00002656702,0.00212352,0.0004240277,0.0001235117,0.00001206279,0.000002811858,0.00007447997],"genre_scores_gemma":[0.9979547,0.0007808169,0.00001194462,0.001075848,0.0001125898,1.660282e-7,0.000005972069,0.00001000481,0.00004795404],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02938503,"threshold_uncertainty_score":0.2850916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02631497986883574,"score_gpt":0.265613589811933,"score_spread":0.2392986099430973,"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."}}