{"id":"W4386127228","doi":"10.1371/journal.pone.0290464","title":"Is scientific evidence enough? Using expert opinion to fill gaps in data in antimicrobial resistance research","year":2023,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Antibiotic Use and Resistance","field":"Immunology and Microbiology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada; University of Guelph; University of Waterloo","funders":"Institute of Population and Public Health; Natural Sciences and Engineering Research Council of Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Canada First Research Excellence Fund; Ministry of Agriculture, Food and Rural Affairs; Ontario Ministry of Agriculture, Food and Rural Affairs; Joint Programming Initiative on Antimicrobial Resistance; Institute of Infection and Immunity; Public Health Agency; Canadian Institutes of Health Research; National Science Foundation; Royal Society; Public Health Agency of Canada; Royal Society of Canada; Vetenskapsrådet","keywords":"Context (archaeology); Data science; Causal loop diagram; Computer science; Knowledge management; Management science; Engineering; Geography; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.5961045,0.002140079,0.005118946,0.03152563,0.006619938,0.02694947,0.009737019,0.01214104,0.008701935],"category_scores_gemma":[0.7773584,0.003128113,0.003766564,0.01380577,0.0196251,0.0413288,0.02228903,0.01260871,0.001495883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02398513,"about_ca_system_score_gemma":0.04821203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007824109,"about_ca_topic_score_gemma":0.01070301,"domain_scores_codex":[0.3015972,0.5746,0.06155526,0.0190664,0.03810352,0.005077563],"domain_scores_gemma":[0.05626796,0.8709322,0.02247597,0.01422978,0.03297411,0.003119943],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006965233,0.0003058517,0.02342201,0.06525777,0.002471962,0.001984743,0.3580028,0.002955253,0.001723927,0.07301353,0.03432753,0.4358381],"study_design_scores_gemma":[0.000497377,0.0007085226,0.0107995,0.1507385,0.002063694,0.0008236948,0.2435768,0.0116434,0.002029641,0.4083929,0.1679451,0.0007808878],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.09105303,0.06839153,0.3262047,0.4553798,0.008086658,0.007164915,0.003419024,0.000667825,0.03963245],"genre_scores_gemma":[0.5804769,0.0207374,0.3385954,0.04517202,0.002018608,0.01014086,0.001496906,0.0002972292,0.001064777],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4038955,"threshold_uncertainty_score":0.4980751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3781641578960576,"score_gpt":0.4061358286569336,"score_spread":0.02797167076087603,"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."}}