{"id":"W2891322772","doi":"10.22079/jmsr.2018.87918.1197","title":"Art to use Electrospun Nanofbers/Nanofber Based Membrane in Waste Water Treatment, Chiral Separation and Desalination","year":2019,"lang":"en","type":"article","venue":"Journal of membrane science and research","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Membrane; Pervaporation; Filtration (mathematics); Desalination; Commercialization; Reverse osmosis; Membrane technology; Nanofiber; Chemical engineering; Nanotechnology; Materials science; Interconnectivity; Process engineering; Chemistry; Polymer science; Chromatography; Permeation; Engineering; Computer 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":[0.0002726202,0.0004722131,0.0002605683,0.0007364292,0.0006158556,0.0005878413,0.0005869746,0.001031256,0.007568891],"category_scores_gemma":[0.0001990665,0.0001973428,0.0005970701,0.0005548473,0.0003566635,0.00121016,0.0005121107,0.0007798341,0.00373456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003702546,"about_ca_system_score_gemma":0.0002533162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002910699,"about_ca_topic_score_gemma":0.0005620182,"domain_scores_codex":[0.9997854,0.00001431385,0.00001477287,0.00004517072,0.0001193427,0.00002104608],"domain_scores_gemma":[0.99994,0.000008719879,0.00001124584,0.00001280359,0.00002114035,0.000006147559],"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":[0.00007247779,0.0002430831,0.0003977896,0.001688672,0.00004031166,0.0004870982,0.0001216892,0.001239297,0.7788142,0.01953999,0.006231104,0.1911242],"study_design_scores_gemma":[0.00002066177,0.0002304821,0.001356621,0.0001972392,0.00003926655,0.001309912,0.00006732771,0.004693068,0.7401214,0.006220362,0.245704,0.00003979221],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2287677,0.1255785,0.3261088,0.006287362,0.005501695,0.0004233354,0.001399497,0.003149701,0.3027834],"genre_scores_gemma":[0.5618926,0.0850812,0.1749524,0.003011304,0.001377594,0.0004753053,0.001212699,0.0004715215,0.1715255],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007568891,"threshold_uncertainty_score":0.02532047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03388500258246586,"score_gpt":0.3410173926854276,"score_spread":0.3071323901029618,"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."}}