{"id":"W4415452711","doi":"10.1021/acsestwater.5c00375","title":"Development of a Method for Assessing Illicit Drug Consumption during Brazilian Carnival through Wastewater-Based Epidemiology Using Gas Chromatography–Mass Spectrometry","year":2025,"lang":"en","type":"article","venue":"ACS ES&T Water","topic":"Forensic Toxicology and Drug Analysis","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"IONICS Mass Spectrometry (Canada)","funders":"Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Illicit drug; Cannabis; MDMA; Ecstasy; Mephedrone; Recreational Drug; Drug; Stimulant; Consumption (sociology)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002497687,0.0004031344,0.0009599809,0.0005837723,0.0007211196,0.00001940747,0.0003150764,0.0005886464,0.0003631304],"category_scores_gemma":[0.000149418,0.0003273837,0.0003604215,0.0003885256,0.0004467103,0.0001930009,0.0001188597,0.0006015084,0.00002034817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001883737,"about_ca_system_score_gemma":0.0001835877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003980412,"about_ca_topic_score_gemma":0.00004789905,"domain_scores_codex":[0.9960037,0.001170492,0.001100322,0.0006512115,0.0001253366,0.000948952],"domain_scores_gemma":[0.9978848,0.001180506,0.0003305245,0.0003369272,0.0001457277,0.0001215537],"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":[0.0005273751,0.0002560112,0.05041262,0.0006406741,0.001429606,0.00001528328,0.001552964,0.00516633,0.9369625,0.001287151,0.0002019603,0.001547454],"study_design_scores_gemma":[0.002445346,0.00003209521,0.002959016,0.00008907758,0.0008011012,0.00001332618,0.000286953,0.009090307,0.977088,0.002730527,0.004103283,0.0003609484],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9263309,0.0003020779,0.07105085,0.0007352466,0.0007752458,0.0004516842,0.00002747377,0.00009453688,0.0002320221],"genre_scores_gemma":[0.7910917,0.0000207767,0.2075041,0.0008935419,0.00008229975,0.00006357004,0.00009491842,0.00002829499,0.0002207159],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1364533,"threshold_uncertainty_score":0.9999178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1023803986071274,"score_gpt":0.4529748855800873,"score_spread":0.3505944869729599,"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."}}