{"id":"W1973490947","doi":"10.1039/c5ra01815c","title":"Poly(acrylic acid) functionalized magnetic graphene oxide nanocomposite for removal of methylene blue","year":2015,"lang":"en","type":"article","venue":"RSC Advances","topic":"Nanomaterials for catalytic reactions","field":"Chemistry","cited_by":98,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Hospital Edmonton; University of Alberta","funders":"Natural Resources Canada","keywords":"Polyacrylic acid; Nanocomposite; Methylene blue; Graphene; Acrylic acid; Adsorption; Oxide; Materials science; Chemical engineering; Nanoparticle; Nuclear chemistry; Polymer chemistry; Polymer; Nanotechnology; Chemistry; Organic chemistry; Composite material; Copolymer; Catalysis; Metallurgy; Photocatalysis","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":[0.00005569154,0.0003409489,0.0001443903,0.0002367452,0.0001335264,0.0001118805,0.0002549996,0.0004193106,0.0009732396],"category_scores_gemma":[0.00008938641,0.0001300032,0.0001812825,0.0001252699,0.000100704,0.0001777316,0.0001496977,0.0003394922,0.0003044429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001721257,"about_ca_system_score_gemma":0.0001119443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000750093,"about_ca_topic_score_gemma":0.002307996,"domain_scores_codex":[0.9999348,0.000006170976,0.000003513076,0.00001535346,0.0000261863,0.00001398327],"domain_scores_gemma":[0.9999646,0.000005913972,0.000009379934,0.000002580183,0.000007842386,0.00000966645],"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":[0.00002516799,0.00001467304,0.00002141568,0.00003072413,0.000003181982,0.00002093228,0.000003693094,0.0000509774,0.9983959,0.00002305218,0.00004003698,0.001370361],"study_design_scores_gemma":[0.000004545034,0.00009825999,0.0007074655,0.000002472926,0.00000978651,0.00004869815,0.000005826741,0.0009895404,0.9971871,0.00001765314,0.0009239832,0.000004809251],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9813575,0.002796699,0.01018025,0.0001979653,0.0001056903,0.00004291495,0.0001891475,0.0004105216,0.004719445],"genre_scores_gemma":[0.9898248,0.0005769718,0.005776347,0.00006690032,0.00001163405,0.00001521467,0.000101128,0.00001642707,0.003610456],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009732396,"threshold_uncertainty_score":0.003255844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01994381787917896,"score_gpt":0.2704976016788125,"score_spread":0.2505537837996336,"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."}}