{"id":"W2803116977","doi":"10.1021/acsami.8b01454","title":"Insight Studies on Metal-Organic Framework Nanofibrous Membrane Adsorption and Activation for Heavy Metal Ions Removal from Aqueous Solution","year":2018,"lang":"en","type":"article","venue":"ACS Applied Materials & Interfaces","topic":"Metal-Organic Frameworks: Synthesis and Applications","field":"Chemistry","cited_by":435,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Polyacrylonitrile; Membrane; Electrospinning; Adsorption; Materials science; Chemical engineering; Metal-organic framework; Nanofiber; Aqueous solution; Metal ions in aqueous solution; Composite number; Scanning electron microscope; Metal; Polymer; Nanotechnology; Composite material; Organic chemistry; Chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001464753,0.0003085786,0.0001341945,0.0002010966,0.0002123276,0.0001341631,0.0002356127,0.0002747767,0.002011908],"category_scores_gemma":[0.0001196868,0.0000902211,0.0002830906,0.0001073557,0.0001437832,0.0002834655,0.0001340511,0.0002453054,0.0002359146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003244943,"about_ca_system_score_gemma":0.0002084267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00199734,"about_ca_topic_score_gemma":0.003089018,"domain_scores_codex":[0.9998863,0.000006623024,0.000004484795,0.00002130355,0.0000436927,0.00003754368],"domain_scores_gemma":[0.9999663,0.000008136401,0.000007941437,0.000002573896,0.00001049557,0.000004593724],"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":[0.00002439292,0.00001371011,0.00007465415,0.00006483164,0.000005195371,0.00003935776,0.00001780648,0.00008867979,0.9973477,0.0001985097,0.00005055314,0.002074588],"study_design_scores_gemma":[0.000003019228,0.00006396088,0.0008751656,0.000002757333,0.000006316844,0.00007502027,0.00001931922,0.0006851659,0.9969797,0.00004137604,0.001244047,0.000004151634],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9831663,0.001961173,0.008603515,0.0001402204,0.00002572502,0.00006983151,0.0002608394,0.0001186341,0.005653691],"genre_scores_gemma":[0.9914768,0.00111164,0.004234526,0.00003552357,0.000006635097,0.00002486498,0.0001586973,0.000008562168,0.002942641],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002011908,"threshold_uncertainty_score":0.006730437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02854824478090608,"score_gpt":0.2728480126009196,"score_spread":0.2442997678200135,"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."}}