{"id":"W2800584776","doi":"10.7939/r3p55dr10","title":"Arsenic Speciation Analysis in Environmental and Biological Systems","year":2013,"lang":"en","type":"article","venue":"University of Alberta Library","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Genetic algorithm; Risk analysis (engineering); Computer science; Environmental science; Biology; Ecology; Business","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001178507,0.0004608927,0.0005708329,0.001529138,0.0005977662,0.001949724,0.000784405,0.0008907422,0.001584078],"category_scores_gemma":[0.0008572923,0.0004063212,0.0005421966,0.001404058,0.0008843409,0.001231281,0.001294123,0.0007533259,0.0009767012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001146985,"about_ca_system_score_gemma":0.0009752459,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00159839,"about_ca_topic_score_gemma":0.001437317,"domain_scores_codex":[0.9986429,0.0003221964,0.00007518865,0.0003661623,0.000517906,0.00007565742],"domain_scores_gemma":[0.9996988,0.00006641485,0.00005829811,0.00003669886,0.0001231678,0.00001663541],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001645128,0.0002517265,0.02134466,0.001827784,0.0004157437,0.0009233041,0.001012664,0.01897764,0.6999186,0.05793169,0.005817938,0.1914137],"study_design_scores_gemma":[0.00003741882,0.0008036835,0.02615699,0.0003034483,0.0002067549,0.001448558,0.001828768,0.06528918,0.6489281,0.04881508,0.2060193,0.0001627439],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3766401,0.02346085,0.5248386,0.005370857,0.0009040189,0.0006561113,0.00236819,0.002307751,0.06345347],"genre_scores_gemma":[0.7342659,0.01877603,0.2167494,0.001272633,0.0003494667,0.0004596086,0.00131557,0.0001906263,0.02662077],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001949724,"threshold_uncertainty_score":0.008322001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004235970825333829,"score_gpt":0.1390449473179654,"score_spread":0.1348089764926316,"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."}}