{"id":"W4382808229","doi":"10.1007/978-3-031-28873-9_7","title":"Biochar-Based Nanocomposites for the Removal of Organic Environmental Contaminants","year":2023,"lang":"en","type":"book-chapter","venue":"Advances in Science, Technology & Innovation/Advances in science, technology & innovation","topic":"Adsorption and biosorption for pollutant removal","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Biochar; Environmental remediation; Nanocomposite; Contamination; Materials science; Environmental science; Environmental chemistry; Waste management; Sorption; Adsorption; Nanotechnology; Chemistry; Organic chemistry; Pyrolysis; Engineering","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":["metaepi_narrow","bibliometrics","sts"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.004033956,0.0008366662,0.000950736,0.01908553,0.001225358,0.00008082543,0.004313926,0.001126184,0.0002648905],"category_scores_gemma":[0.001213669,0.000718965,0.0001126883,0.0529497,0.03187856,0.002710764,0.001294596,0.001347607,0.0001764603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001588709,"about_ca_system_score_gemma":0.0005616454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004565333,"about_ca_topic_score_gemma":0.0002219094,"domain_scores_codex":[0.9916947,0.0000229333,0.002642098,0.002284719,0.001945368,0.001410122],"domain_scores_gemma":[0.9951683,0.0002791607,0.002421876,0.001576708,0.0004985007,0.00005541199],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005929109,0.0001188951,0.009665838,0.00002731896,0.000008603753,0.00001782517,0.00004561273,0.0005780646,0.4583115,0.4370835,0.00002891054,0.09405465],"study_design_scores_gemma":[0.003025576,0.0009922447,0.001981768,0.000653606,0.00005833359,0.0002887534,0.00135433,0.00194924,0.3474887,0.3630674,0.2770953,0.0020448],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8984609,0.006498712,0.01567097,0.006971554,0.00510359,0.007536173,0.0004522701,0.001763967,0.0575419],"genre_scores_gemma":[0.9728603,0.002374882,0.01038939,0.0004160088,0.00005872149,0.0003451618,0.00008621554,0.00009893668,0.01337039],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2770663,"threshold_uncertainty_score":0.9995261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.011544532390454,"score_gpt":0.2703048577153898,"score_spread":0.2587603253249358,"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."}}