{"id":"W4307030595","doi":"10.1002/adfm.202207723","title":"Metal‐Organic Frameworks and Electrospinning: A Happy Marriage for Wastewater Treatment","year":2022,"lang":"en","type":"article","venue":"Advanced Functional Materials","topic":"Metal-Organic Frameworks: Synthesis and Applications","field":"Chemistry","cited_by":216,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"University of British Columbia; Canada Research Chairs","keywords":"Materials science; Electrospinning; Metal-organic framework; Nanofiber; Wastewater; Adsorption; Photodegradation; Metal ions in aqueous solution; Nanotechnology; Sewage treatment; Aqueous solution; Water treatment; Portable water purification; Photocatalysis; Waste management; Chemical engineering; Metal; Polymer; Composite material; Organic chemistry; Catalysis; Metallurgy; 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":[0.0006503102,0.0005225101,0.0005565587,0.0005078863,0.0003885249,0.0008210356,0.0004707843,0.001043368,0.001992858],"category_scores_gemma":[0.0003966121,0.0002540205,0.0003933946,0.0004515907,0.0004780104,0.002163937,0.0007766093,0.00141765,0.0008534522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003739131,"about_ca_system_score_gemma":0.000424996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002127382,"about_ca_topic_score_gemma":0.0005998551,"domain_scores_codex":[0.9996971,0.00005458914,0.00001463237,0.00005373923,0.000133432,0.00004652588],"domain_scores_gemma":[0.9998491,0.00005854078,0.00002432793,0.000007650561,0.0000329745,0.00002735161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00021721,0.0002570079,0.0004600388,0.005377824,0.0001527619,0.00102979,0.0004482687,0.0009871067,0.2405669,0.06171727,0.0371987,0.6515872],"study_design_scores_gemma":[0.00004453573,0.0005510495,0.0009378885,0.0008219897,0.00006799467,0.001314992,0.0003502146,0.001392385,0.08018558,0.02720631,0.8870327,0.00009423574],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.01483946,0.9383348,0.02250632,0.008463763,0.003386102,0.00003249689,0.0000978497,0.0002723257,0.01206676],"genre_scores_gemma":[0.1294152,0.8030832,0.03814346,0.004514775,0.00341581,0.000106726,0.0002160822,0.0001005856,0.02100415],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001992858,"threshold_uncertainty_score":0.00666678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01371478093003831,"score_gpt":0.2369618947050223,"score_spread":0.223247113774984,"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."}}