{"id":"W3000470641","doi":"10.21577/0103-5053.20200004","title":"Determination of Copper and Cadmium in Petroleum Produced Formation Water by Electrothermal Atomic Absorption Spectrometry after Cloud Point Extraction","year":2020,"lang":"en","type":"article","venue":"Journal of the Brazilian Chemical Society","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundação de Amparo à Pesquisa do Estado da Bahia; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Financiadora de Estudos e Projetos; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Cadmium; Cloud point; Atomic absorption spectroscopy; Copper; Chemistry; Extraction (chemistry); Environmental chemistry; Analytical Chemistry (journal); Chromatography; Physics; Organic chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004135631,0.0001533157,0.0002729537,0.00001573271,0.00002799392,0.00002149826,0.0001793879,0.0001801782,0.0001992454],"category_scores_gemma":[0.0001460741,0.0001040478,0.000232181,0.000111596,0.00007709807,0.0002437487,0.00006804113,0.0005735726,0.000001788268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004119719,"about_ca_system_score_gemma":0.00003923558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001511645,"about_ca_topic_score_gemma":2.164469e-7,"domain_scores_codex":[0.998564,0.0000362724,0.0006417193,0.0001756262,0.0003590356,0.0002233684],"domain_scores_gemma":[0.9992853,0.00005480571,0.0003502884,0.0001155683,0.00008369158,0.0001102942],"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":[0.0002212921,0.00006279484,0.001397519,0.0002277746,0.00002651465,0.000001402925,0.0006802282,0.0000012526,0.9964103,8.358406e-7,0.0005406741,0.0004294286],"study_design_scores_gemma":[0.0007114481,0.0000192879,0.0005407137,0.00007230395,0.00004329951,0.00006670145,0.0001798262,0.001898349,0.9959487,0.0001547986,0.0002430208,0.000121538],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935309,0.00009565916,0.002742729,0.003417873,0.00004336338,0.00005978758,0.000004808379,0.000008305345,0.00009652918],"genre_scores_gemma":[0.9948533,0.00003570438,0.004567249,0.0002191538,0.0002264683,0.000004144125,0.000005753656,0.00001661093,0.00007163539],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003198719,"threshold_uncertainty_score":0.4242945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008076515864505243,"score_gpt":0.2449126296368319,"score_spread":0.2368361137723267,"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."}}