{"id":"W2899618451","doi":"10.1016/j.biortech.2018.11.023","title":"Piggery wastewater treatment by aerobic granular sludge: Granulation process and antibiotics and antibiotic-resistant bacteria removal and transport","year":2018,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":103,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Fundamental Research Funds for the Central Universities; Major Science and Technology Program for Water Pollution Control and Treatment; National Natural Science Foundation of China","keywords":"Antibiotics; Chemistry; Granulation; Extracellular polymeric substance; Bioreactor; Tetracycline; Microbiology; Aerobic bacteria; Wastewater; Food science; Bacteria; Biology; Biofilm; Biochemistry; Environmental engineering; Organic chemistry; Materials 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":[0.0003296605,0.0003622219,0.0003979499,0.0002301496,0.0002245934,0.0007158602,0.0002591066,0.0007189624,0.0008121077],"category_scores_gemma":[0.0002880674,0.0001526933,0.000678579,0.0002390467,0.0003553004,0.0004244351,0.0002410787,0.0003193077,0.0001522415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007127248,"about_ca_system_score_gemma":0.0005142696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004737495,"about_ca_topic_score_gemma":0.004495556,"domain_scores_codex":[0.9997516,0.00005623768,0.00002241501,0.0000401503,0.00004868716,0.00008085115],"domain_scores_gemma":[0.9998941,0.00003135116,0.000028048,0.00000748997,0.00001906019,0.00001987138],"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":[0.001738525,0.00028712,0.003018856,0.0001334303,0.00004652866,0.0002054439,0.0000582593,0.000816559,0.9866797,0.0001334965,0.00006190957,0.006820046],"study_design_scores_gemma":[0.00007342241,0.002449575,0.02499392,0.00001544702,0.0001029634,0.000217261,0.0001752248,0.005192572,0.9656425,0.0002001983,0.0009148863,0.00002197676],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986506,0.0003639199,0.0004527349,0.00005100495,0.0000263938,0.000007488906,0.00002362622,0.000008335045,0.0004159698],"genre_scores_gemma":[0.9985992,0.0002069165,0.0003203151,0.00002303947,0.000006229113,0.000003147484,0.00003558414,0.000002889848,0.0008027034],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004737495,"threshold_uncertainty_score":0.009419858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009833619857507529,"score_gpt":0.2414671496960544,"score_spread":0.2316335298385468,"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."}}