{"id":"W4220893185","doi":"10.1016/j.surfin.2022.101880","title":"Malachite green removal using algal biochar and its composites with kombucha SCOBY: An integrated biosorption and phycoremediation approach","year":2022,"lang":"en","type":"article","venue":"Surfaces and Interfaces","topic":"Adsorption and biosorption for pollutant removal","field":"Environmental Science","cited_by":55,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Biotechnology Industry Research Assistance Council; National Institute of Technology Rourkela; Department of Biotechnology, Ministry of Science and Technology, India","keywords":"Malachite green; Biochar; Adsorption; Wastewater; Biosorption; Pulp and paper industry; Environmental engineering; Environmental chemistry; Chemistry; Materials science; Chemical engineering; Environmental science; Pyrolysis; Organic chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002722811,0.0002167246,0.0001867697,0.0000791161,0.0004016333,0.0001044676,0.0001053672,0.00005507611,0.0003576718],"category_scores_gemma":[0.000004296805,0.0001684879,0.00001736928,0.0002275075,0.0002459419,0.0004899628,0.0002478734,0.000179464,0.000007488292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006114686,"about_ca_system_score_gemma":0.000008513657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005480318,"about_ca_topic_score_gemma":0.00008026998,"domain_scores_codex":[0.9986802,0.0001336248,0.0001984472,0.0004677998,0.0002966018,0.0002232896],"domain_scores_gemma":[0.999602,0.00001416718,0.0001361525,0.00009975006,0.00001343263,0.0001345387],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000327471,0.0001199167,0.03107026,0.0000310297,0.00003320278,0.000005722456,0.001515907,0.002449561,0.9572003,0.0001320744,0.00003442564,0.007080096],"study_design_scores_gemma":[0.00232035,0.002454872,0.05739436,0.0000728257,0.000133916,0.001557828,0.007531076,0.8567081,0.06467123,0.0001355937,0.005730493,0.001289333],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981645,0.0006936849,0.000201539,0.0001997809,0.00006141258,0.0002638107,0.00008320372,0.00006025715,0.0002717843],"genre_scores_gemma":[0.997,0.0001277643,0.002341865,0.00009397133,0.00002174517,0.000004773907,0.00005597839,0.00001761045,0.0003363226],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8925291,"threshold_uncertainty_score":0.6870737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01685361307304151,"score_gpt":0.2202116042568429,"score_spread":0.2033579911838014,"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."}}