{"id":"W2463214277","doi":"10.5935/0103-5053.20160039","title":"UV-Assisted Digestion of Petrochemical Industry Effluents Prior to the Determination of Zn, Cd, Pb and Cu by Differential Pulse Anodic Stripping Voltammetry","year":2016,"lang":"en","type":"article","venue":"Journal of the Brazilian Chemical Society","topic":"Electrochemical Analysis and Applications","field":"Chemistry","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Espace pour la vie","funders":"Fundação de Amparo à Pesquisa do Estado da Bahia; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Anodic stripping voltammetry; Stripping (fiber); Petrochemical; Effluent; Voltammetry; Anode; Environmental chemistry; Chemistry; Environmental science; Materials science; Electrode; Environmental engineering; Electrochemistry","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":[0.0002046742,0.0001834005,0.0003756568,0.00002157982,0.0001049275,0.00002397521,0.000589325,0.0003624663,0.00008449818],"category_scores_gemma":[0.0003856637,0.00009608307,0.0004844918,0.0003167988,0.0002408823,0.00008764696,0.000188386,0.0006186199,8.890458e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000167942,"about_ca_system_score_gemma":0.00005317679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006524911,"about_ca_topic_score_gemma":8.618517e-7,"domain_scores_codex":[0.9982334,0.00002938682,0.0007454674,0.0002183951,0.0005327263,0.0002405914],"domain_scores_gemma":[0.9982886,0.0002599162,0.0007681727,0.0003056223,0.000210086,0.0001675519],"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":[0.00004732576,0.0001855127,0.004694713,0.00006219152,0.00009655746,1.168184e-7,0.00007072435,2.20076e-7,0.9790537,0.000004728296,0.001948295,0.0138359],"study_design_scores_gemma":[0.0007238754,0.0000200317,0.00286145,0.0002831199,0.0002024091,0.00001861444,0.00006874728,0.0001027925,0.9951065,0.0001276462,0.0003677318,0.0001170868],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956413,0.0001320625,0.001324604,0.00271422,0.00002599613,0.00007176835,0.00004329436,0.000007401655,0.00003934866],"genre_scores_gemma":[0.9988881,0.00005194719,0.0005081969,0.0001009445,0.0001863627,0.000006185604,0.000006735808,0.00001538774,0.0002361372],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01605278,"threshold_uncertainty_score":0.3918154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006652316915843622,"score_gpt":0.238546332683036,"score_spread":0.2318940157671924,"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."}}