{"id":"W2989943796","doi":"10.1016/j.scitotenv.2019.135365","title":"Graphene-based electro-conductive anti-fouling membranes for the treatment of oil sands produced water","year":2019,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":67,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Resources Canada; Natural Sciences and Engineering Research Council of Canada; Stillborn and Neonatal Death Charity","keywords":"Membrane; Materials science; Fouling; Chemical engineering; Biofouling; Anode; Polyaniline; Oxide; Graphene; Composite material; Electrode; Nanotechnology; Chemistry; Metallurgy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007294832,0.000180966,0.0002057161,0.00003890618,0.0003906892,0.00002000515,0.001058498,0.00003867035,0.0004103769],"category_scores_gemma":[0.00003075873,0.00006961235,0.0001641758,0.0002685167,0.002372147,0.0001580274,0.0002043041,0.00006867366,0.00006566766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001833591,"about_ca_system_score_gemma":0.00002404797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000758283,"about_ca_topic_score_gemma":0.000001083609,"domain_scores_codex":[0.9982557,0.0000501645,0.0002666762,0.0004009018,0.0006482671,0.0003783158],"domain_scores_gemma":[0.9985578,0.0001244039,0.000186575,0.00109476,0.000008010016,0.00002845058],"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":[0.00003665004,0.0001064849,0.0001446656,0.000009837559,0.00001544622,3.867446e-8,0.0005990949,0.1848552,0.8128616,0.00005985802,0.000007034133,0.001304042],"study_design_scores_gemma":[0.0004156097,0.0003595298,0.002595469,0.000006832065,0.00004443688,0.000002004281,0.0002901561,0.00710514,0.9883952,0.0003861602,0.0002940479,0.0001054119],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959586,0.0001112942,0.0000327415,0.002453233,0.0001760473,0.0008172886,0.000006396296,0.00001880956,0.0004256318],"genre_scores_gemma":[0.9982264,0.0001119115,0.0002980944,0.00002056137,0.00001144083,0.00009461513,0.000001014135,0.00001037902,0.001225585],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1777501,"threshold_uncertainty_score":0.8740275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01311809266243032,"score_gpt":0.2224494330990397,"score_spread":0.2093313404366094,"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."}}