{"id":"W2976644338","doi":"10.1016/j.jenvman.2019.109551","title":"Activated carbon biochar from municipal waste as a sorptive agent for the removal of polyaromatic hydrocarbons (PAHs), phenols and petroleum based compounds in contaminated liquids","year":2019,"lang":"en","type":"article","venue":"Journal of Environmental Management","topic":"Adsorption and biosorption for pollutant removal","field":"Environmental Science","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hendrix Genetics (Canada)","funders":"","keywords":"Biochar; Petroleum; Environmental chemistry; Chemistry; Phenols; Waste management; Activated carbon; Petroleum product; Environmental science; Carbon fibers; Contamination; Pollutant; Pyrolysis; Organic chemistry; Adsorption; Materials science","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":[0.000479685,0.0002350463,0.0003631728,0.000140189,0.00005526601,0.00002214359,0.0003261621,0.00007562341,0.0005518569],"category_scores_gemma":[0.000009014336,0.000172944,0.0001585811,0.0001350047,0.0002434756,0.0001328223,0.0002206241,0.0001829453,0.00002851887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003855799,"about_ca_system_score_gemma":0.000006988175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002054207,"about_ca_topic_score_gemma":0.00002803417,"domain_scores_codex":[0.998166,0.0001260152,0.0006334763,0.0002579491,0.0005478244,0.0002687638],"domain_scores_gemma":[0.998955,0.0001410219,0.0005480521,0.0002624956,0.000002341613,0.00009113837],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001151427,0.0006302717,0.005382745,0.00003081684,0.0002879261,0.00007668516,0.0007209948,0.002179469,0.9862635,0.00007177793,0.00005651688,0.00314793],"study_design_scores_gemma":[0.03748628,0.007818825,0.3711669,0.001251815,0.001561845,0.0004697263,0.03782516,0.2674036,0.2547923,0.001752546,0.01633158,0.002139511],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968547,0.0002486201,0.0001183497,0.0003742084,0.0001606593,0.0006795707,0.00004210637,0.000006690097,0.001515106],"genre_scores_gemma":[0.9982238,0.0001526475,0.0005081517,0.0002420378,0.00002454996,0.00001001977,0.00001081138,0.00002157084,0.0008063888],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7314712,"threshold_uncertainty_score":0.7052452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007224862020977773,"score_gpt":0.2065755540224146,"score_spread":0.1993506920014368,"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."}}