{"id":"W2932689066","doi":"10.11159/icnnfc19.109","title":"A Cumulene/CNTs Nanocomposite for Removal of Organic Dyes from Aquatic Media","year":2019,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Recent Advances in Nanotechnology","topic":"Adsorption and biosorption for pollutant removal","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Ministry of Science and Higher Education of the Russian Federation","keywords":"Nanocomposite; Cumulene; Materials science; Carbon nanotube; Composite material; Nanotechnology; Chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009597265,0.0002497066,0.0001459164,0.0002393194,0.0001908197,0.0002185075,0.0001993526,0.0002909306,0.0007766277],"category_scores_gemma":[0.0001351763,0.0001247701,0.0001526555,0.00008494881,0.0001019059,0.0002220648,0.0001810782,0.0002611525,0.0002211231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002166506,"about_ca_system_score_gemma":0.0001574855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008780119,"about_ca_topic_score_gemma":0.003619755,"domain_scores_codex":[0.9999472,0.000004859455,0.000002802348,0.00001445862,0.00002094282,0.000009669463],"domain_scores_gemma":[0.9999428,0.00001211084,0.00000873152,0.000004422084,0.00001410018,0.0000179085],"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":[0.00004535208,0.0000275753,0.00006317082,0.00003029553,0.000003066328,0.0000324159,0.000008286052,0.0001086718,0.9971244,0.00004130567,0.00004459943,0.002470866],"study_design_scores_gemma":[0.000005689804,0.0001360992,0.0007301557,0.000002540148,0.000008251375,0.00004226705,0.000004360931,0.002377683,0.99562,0.00001259147,0.001056489,0.000003824423],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927551,0.0008806136,0.003738869,0.00007636873,0.00005114623,0.00002802975,0.0000491201,0.0001056411,0.002315032],"genre_scores_gemma":[0.9885587,0.0005527689,0.004437797,0.00004986662,0.00001857136,0.0000154818,0.00006649728,0.000028002,0.006272269],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008780119,"threshold_uncertainty_score":0.002598047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007261086326708786,"score_gpt":0.2363307054127698,"score_spread":0.229069619086061,"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."}}