{"id":"W952426436","doi":"10.1007/0-306-46921-9_12","title":"Removal of Nitroaromatic Compounds from Water through Combined Zero-valent Metal Reduction and Enzyme-based Oxidative Coupling Reactions","year":2005,"lang":"en","type":"book-chapter","venue":"Kluwer Academic Publishers eBooks","topic":"Environmental remediation with nanomaterials","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Division of Human Resource Development; Natural Sciences and Engineering Research Council of Canada; Ministry of Health and Medical Education","keywords":"Nitrobenzene; Aniline; Chemistry; Zerovalent iron; Oxidative coupling of methane; Catalysis; Aqueous solution; Peroxidase; Oxidative phosphorylation; Phenols; Oxygen; Photochemistry; Inorganic chemistry; Organic chemistry; Enzyme; Biochemistry","routes":{"ca_aff":true,"ca_fund":true,"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"],"consensus_categories":[],"category_scores_codex":[0.0003760631,0.0006523716,0.0008838145,0.0003075179,0.0001043323,0.0001203692,0.0003323819,0.0009918894,0.0003934546],"category_scores_gemma":[0.00003203727,0.0006156723,0.0001817206,0.00002645615,0.0003710341,0.0008796866,0.0001151926,0.001040515,0.00004599934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005474387,"about_ca_system_score_gemma":0.00004825546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004390361,"about_ca_topic_score_gemma":0.000002003451,"domain_scores_codex":[0.997055,0.00003721627,0.001279054,0.0005604723,0.0006500958,0.000418144],"domain_scores_gemma":[0.9987106,0.0001474116,0.0004467994,0.0004708984,0.00005893995,0.0001653239],"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":[0.0001630031,0.00003941541,0.00001652148,0.0004130141,0.001212941,0.00002282122,0.002072578,0.004785682,0.9758463,0.001340857,0.01328265,0.0008042248],"study_design_scores_gemma":[0.003878153,0.0001733846,0.00006806134,0.001188427,0.001276648,0.0001352196,0.000278873,0.004483026,0.7850689,0.02099046,0.1804581,0.002000766],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5280933,0.002571446,0.002160636,0.0005045049,0.005239245,0.003104717,0.0007287354,0.001447437,0.4561499],"genre_scores_gemma":[0.90776,0.0002050324,0.004938382,0.0001417359,0.0007987738,0.0001199362,0.00155618,0.0004144486,0.08406553],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3796667,"threshold_uncertainty_score":0.9996294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0181525399359508,"score_gpt":0.2160471710260803,"score_spread":0.1978946310901295,"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."}}