{"id":"W1059875913","doi":"10.1016/j.seppur.2015.08.001","title":"Copper ion removal from dilute solutions using colloidal liquid aphrons","year":2015,"lang":"en","type":"article","venue":"Separation and Purification Technology","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Copper; Colloid; Ion; Chemical engineering; Colloidal particle; Chemistry; Chromatography; Materials science; Organic chemistry; Engineering","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":[0.0001799305,0.0002834706,0.0002868141,0.0003048544,0.0002945274,0.0004745615,0.0002884571,0.0003516479,0.0006118666],"category_scores_gemma":[0.0002779777,0.0001844724,0.000168642,0.0001841659,0.0001881631,0.0002874616,0.0002689053,0.0005526688,0.0004352184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002878612,"about_ca_system_score_gemma":0.0003139545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001034232,"about_ca_topic_score_gemma":0.001188655,"domain_scores_codex":[0.9998189,0.00002188607,0.00001420898,0.00003710321,0.00007478126,0.00003324128],"domain_scores_gemma":[0.9999027,0.00002891569,0.00001323193,0.00001125478,0.00002951059,0.00001425273],"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":[0.00002376971,0.000006467459,0.00003069919,0.00002233463,0.000001868882,0.00002840471,0.00001392084,0.00004655771,0.9979797,0.00006252377,0.00004415497,0.001739561],"study_design_scores_gemma":[0.000004917491,0.00003144459,0.0001137666,0.000001389176,0.000002466036,0.00002967686,0.000006966683,0.0005274699,0.9986938,0.00002125861,0.0005648177,0.000002147782],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9634963,0.00119998,0.03089332,0.0001883398,0.00007438166,0.00004526409,0.00006913023,0.0003802917,0.003653087],"genre_scores_gemma":[0.9729006,0.0006475116,0.01838529,0.00009039245,0.00003438379,0.000029205,0.00009560065,0.00006147979,0.007755655],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001034232,"threshold_uncertainty_score":0.002088606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04456298745252484,"score_gpt":0.2912069571552883,"score_spread":0.2466439697027634,"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."}}