{"id":"W4375930235","doi":"10.2139/ssrn.4442165","title":"High Perm-Selectivity and Performance of Tuned Nanofiltration Membranes by Merging Carbon Nitride Derivatives as Interphase Layer for Efficient Separation of Dye and Salt","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Chemical Synthesis and Characterization","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Nanofiltration; Interphase; Selectivity; Membrane; Separation (statistics); Layer (electronics); Materials science; Chemical engineering; Salt (chemistry); Nitride; Carbon fibers; Chromatography; Nanotechnology; Chemistry; Composite material; Organic chemistry; Computer science; Catalysis; Engineering; Composite number","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":[0.0007070666,0.0001737178,0.0002903707,0.00005601797,0.00009513638,0.00002777283,0.0001046148,0.0001162966,0.00001239739],"category_scores_gemma":[0.00009035655,0.0001570826,0.00005661323,0.00009942296,0.00009555509,0.0001022708,0.0001050231,0.0004024459,3.322033e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003305132,"about_ca_system_score_gemma":0.0001287522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003256311,"about_ca_topic_score_gemma":0.0001155147,"domain_scores_codex":[0.998598,0.00006267524,0.0003694112,0.000284801,0.0002332728,0.000451776],"domain_scores_gemma":[0.9992635,0.000102754,0.0004625079,0.00009360194,0.0000333394,0.00004431711],"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":[0.0002480809,0.00006661654,0.005360628,0.0001134612,0.00005550211,7.927432e-8,0.0003425214,0.001063511,0.9875225,0.0001024849,0.000002858315,0.005121712],"study_design_scores_gemma":[0.0004712459,0.0003615629,0.008624669,0.0001374279,0.00007679606,0.00001645656,0.0001638564,0.02686502,0.9589491,0.004111534,0.000009755091,0.0002125085],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965929,0.0003124143,0.002563525,0.0001328564,0.0000653199,0.0002832956,0.00002064966,0.00001161323,0.00001746766],"genre_scores_gemma":[0.9973675,0.002354926,0.0000755961,0.000006441137,0.00004004101,0.00002253136,0.00004002389,0.00001944828,0.00007351349],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02857337,"threshold_uncertainty_score":0.6405643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00810335246578756,"score_gpt":0.2435675189519263,"score_spread":0.2354641664861388,"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."}}