{"id":"W2007042296","doi":"10.1021/ac000527u","title":"Speciation of Key Arsenic Metabolic Intermediates in Human Urine","year":2000,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":331,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Arsenic; Chemistry; Arsenite; Arsenate; Genetic algorithm; Urine; Metabolic pathway; Environmental chemistry; Arsenobetaine; Chromatography; Metabolism; Biochemistry; Organic chemistry; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002566411,0.0002927294,0.0001559758,0.0005616114,0.000291292,0.0002367768,0.0002009359,0.0004429931,0.0008722001],"category_scores_gemma":[0.0004887948,0.0001366276,0.0001427258,0.0003023337,0.0002051363,0.0001627859,0.0001887069,0.0001872051,0.0004891269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001475675,"about_ca_system_score_gemma":0.0003450165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007326929,"about_ca_topic_score_gemma":0.0009070406,"domain_scores_codex":[0.9998028,0.00006250533,0.000009839693,0.0000462774,0.00005979051,0.00001875564],"domain_scores_gemma":[0.9998984,0.00002552987,0.00002030574,0.000007185871,0.00003480579,0.00001374466],"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":[0.000290418,0.00003634536,0.007122958,0.0001100056,0.00002503298,0.0001901861,0.0001040028,0.0001142413,0.9699088,0.0002215735,0.0002742462,0.02160219],"study_design_scores_gemma":[0.00000872162,0.000440221,0.01480194,0.00001182282,0.00002559507,0.001458471,0.0001088913,0.0005867947,0.9783562,0.0002928633,0.003894836,0.00001365771],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9157925,0.009211429,0.06720529,0.0004451734,0.0001067,0.0001949006,0.001343467,0.001195342,0.004505238],"genre_scores_gemma":[0.9285036,0.004001949,0.06192776,0.0002685699,0.00003346979,0.00008606174,0.0006277103,0.00005721653,0.004493715],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008722001,"threshold_uncertainty_score":0.002917767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005428721724744017,"score_gpt":0.2299976780077471,"score_spread":0.2245689562830031,"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."}}