{"id":"W2804424607","doi":"10.1089/ees.2017.0520","title":"An Environmental Science and Engineering Framework for Combating Antimicrobial Resistance","year":2018,"lang":"en","type":"article","venue":"Environmental Engineering Science","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of Alberta","funders":"National Science Foundation","keywords":"Resistance (ecology); Identification (biology); Agriculture; Antibiotic resistance; Environmental planning; Public health; Engineering ethics; Engineering; Risk analysis (engineering); Environmental resource management; Medicine; Ecology; Environmental science","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":[0.01071566,0.00216944,0.001037007,0.004612529,0.00404813,0.01144882,0.003928723,0.007596179,0.007767082],"category_scores_gemma":[0.005488265,0.0007703229,0.001739569,0.001855085,0.0183615,0.009357662,0.00898222,0.005602131,0.0009007015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01026998,"about_ca_system_score_gemma":0.01721582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009178312,"about_ca_topic_score_gemma":0.01062084,"domain_scores_codex":[0.9935772,0.003579361,0.0002970763,0.000617459,0.001213027,0.0007160041],"domain_scores_gemma":[0.9961073,0.001776507,0.0003613216,0.000295586,0.000839997,0.0006192097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000005224044,0.00003481217,0.0001474519,0.00009039781,0.000009157123,0.00009941968,0.0002454623,0.006027533,0.000188542,0.9868732,0.001851191,0.004427646],"study_design_scores_gemma":[0.00000970475,0.00003679233,0.0001280139,0.0001907039,0.00001032546,0.00005878849,0.000803515,0.005582656,0.0001841736,0.9220125,0.07096345,0.00001934675],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01171474,0.02743732,0.3660668,0.2132618,0.002825635,0.0005333311,0.0003343706,0.0003119723,0.3775141],"genre_scores_gemma":[0.614895,0.02801444,0.2955285,0.01452265,0.002687612,0.001461651,0.0004088244,0.0001854403,0.04229592],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01144882,"threshold_uncertainty_score":0.07451433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00867833925122346,"score_gpt":0.2430691466010543,"score_spread":0.2343908073498308,"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."}}