{"id":"W2521659978","doi":"10.1016/j.jes.2016.07.014","title":"Efficient degradation of chlorobenzene in a non-thermal plasma catalytic reactor supported on CeO 2 /HZSM-5 catalysts","year":2016,"lang":"en","type":"article","venue":"Journal of Environmental Sciences","topic":"Catalytic Processes in Materials Science","field":"Materials Science","cited_by":56,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"National Natural Science Foundation of China","keywords":"Chlorobenzene; Catalysis; Selectivity; Chemistry; Decomposition; Fourier transform infrared spectroscopy; Nonthermal plasma; Adsorption; Scanning electron microscope; Thermal stability; Chemical engineering; Inorganic chemistry; Materials science; Organic chemistry; Plasma; Composite material","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001998535,0.0002331621,0.0003842544,0.0001710498,0.0001626585,0.0003636613,0.0003560538,0.0002950896,0.0005497243],"category_scores_gemma":[0.0001867028,0.000148683,0.0001970535,0.0001077835,0.0002462216,0.0002055602,0.0001816684,0.0002693805,0.0001588771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003812576,"about_ca_system_score_gemma":0.0002514724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001823563,"about_ca_topic_score_gemma":0.002602356,"domain_scores_codex":[0.9998332,0.00001523504,0.000008140154,0.00002722117,0.00005776136,0.00005835852],"domain_scores_gemma":[0.999927,0.00002297435,0.00001208691,0.000009181109,0.00001628868,0.00001245098],"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":[0.000163275,0.00001175257,0.000174445,0.00003888884,0.000004791762,0.00004819418,0.00002227288,0.0001059898,0.9984364,0.00004500824,0.00002673624,0.0009222958],"study_design_scores_gemma":[0.000008679631,0.00007538444,0.0008682201,0.000001503308,0.000005168096,0.00003066863,0.00001198652,0.000871052,0.997927,0.000006671998,0.0001911009,0.000002644249],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985232,0.0003108452,0.0006007289,0.0000223206,0.000007564622,0.000004074694,0.00002813312,0.00002832652,0.0004748768],"genre_scores_gemma":[0.999294,0.00008208452,0.0002106257,0.000005065969,0.00000152191,0.000001423905,0.00002247975,0.000004322368,0.0003783798],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001823563,"threshold_uncertainty_score":0.00362587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01066762275380099,"score_gpt":0.2343611590141594,"score_spread":0.2236935362603584,"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."}}