{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001196838,0.0003040986,0.0003100462,0.00008646195,0.0002355303,0.00003515467,0.0001221682,0.0002501359,0.00010437],"category_scores_gemma":[0.00001137322,0.0002373895,0.0000265518,0.0002048036,0.002214561,0.0001367854,0.0001276793,0.0001160197,0.00003275441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005900369,"about_ca_system_score_gemma":0.000003586617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006004801,"about_ca_topic_score_gemma":0.0000241254,"domain_scores_codex":[0.9984823,0.00003052818,0.0002537842,0.00059733,0.000159049,0.0004769733],"domain_scores_gemma":[0.9994501,0.00001694803,0.00007662171,0.0002409823,0.000004329397,0.0002110606],"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":[0.00008887244,0.000141305,0.1939819,0.0000309456,0.00001665601,0.00003541615,0.0001934556,5.508777e-7,0.797763,0.00003477918,0.00005331306,0.00765972],"study_design_scores_gemma":[0.001526099,0.001026819,0.2437177,0.00005572635,0.0001244741,0.0003035076,0.0001803541,0.0003585095,0.738664,0.0003642514,0.01318685,0.0004917039],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976643,0.0003417371,0.00002888724,0.00120398,0.00003794141,0.0003063893,0.00003116653,0.0001202907,0.0002653438],"genre_scores_gemma":[0.9985284,0.0003217687,0.0007605455,0.0001559193,0.00003116614,4.541696e-7,0.00001969041,0.00002754818,0.0001545103],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.059099,"threshold_uncertainty_score":0.9680462,"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."}}