{"id":"W2323704915","doi":"10.1021/es101417u","title":"Role of Detection Limits in Drinking Water Regulation","year":2010,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Environmental Justice and Health Disparities","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Concordia University; U.S. Environmental Protection Agency","keywords":"Context (archaeology); Safe Drinking Water Act; Environmental regulation; Regulatory agency; Agency (philosophy); Maximum Contaminant Level; Process (computing); Environmental planning; Risk analysis (engineering); Business; Environmental science; Water quality; Groundwater; Computer science; Engineering; Political science; Ecology","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":[0.1412538,0.0008936066,0.001527834,0.004487897,0.003756304,0.01275863,0.008203042,0.01237996,0.0030472],"category_scores_gemma":[0.3602751,0.001217605,0.003305863,0.003357253,0.02712058,0.01332915,0.007328771,0.01444933,0.0004134261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0123396,"about_ca_system_score_gemma":0.01440033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01879462,"about_ca_topic_score_gemma":0.01032135,"domain_scores_codex":[0.8136714,0.08998954,0.01379283,0.0197885,0.05523705,0.00752072],"domain_scores_gemma":[0.5036701,0.4133874,0.03048272,0.01918875,0.03088666,0.00238438],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001067559,0.00006475126,0.01161886,0.0004276047,0.0001446047,0.0001560648,0.001852689,0.004578505,0.0006598214,0.9531484,0.007960214,0.01928175],"study_design_scores_gemma":[0.0001478996,0.0003875119,0.02502722,0.002947664,0.0004794337,0.0005554484,0.002576206,0.0129466,0.008137352,0.7954467,0.150883,0.000464973],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1152177,0.02911486,0.1424653,0.3889037,0.004666981,0.0003843365,0.00114422,0.0006557819,0.3174471],"genre_scores_gemma":[0.925324,0.002873853,0.02007624,0.04577421,0.001757813,0.0003144094,0.0001087841,0.0001214868,0.003649133],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1412538,"threshold_uncertainty_score":0.7470306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006165170396278569,"score_gpt":0.2465558992740994,"score_spread":0.2403907288778208,"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."}}