{"id":"W2126272514","doi":"10.1111/j.1745-6584.2008.00464.x","title":"Risk Management of BTEX Contamination in Ground Water—An Integrated Fuzzy Approach","year":2008,"lang":"en","type":"article","venue":"Ground Water","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"BTEX; Risk assessment; Fuzzy logic; Risk analysis (engineering); Computer science; Risk management; Contamination; Environmental science; Reliability engineering; Engineering; Business; Artificial intelligence; Xylene","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004758437,0.0002295575,0.0002651434,0.0001062098,0.0002170739,0.0000358035,0.0002670249,0.00008210661,0.0003274566],"category_scores_gemma":[0.000002018992,0.0001420408,0.00006325424,0.0001640143,0.0002528168,0.000615938,0.0002372357,0.0001418816,0.0003618161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002318515,"about_ca_system_score_gemma":0.000002171783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002523833,"about_ca_topic_score_gemma":0.0003215879,"domain_scores_codex":[0.9981371,0.0001568656,0.0004244944,0.0004442266,0.0004033335,0.0004340194],"domain_scores_gemma":[0.9995351,0.00001140469,0.00006239935,0.0003027314,0.00002529786,0.0000629947],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005012889,0.0038127,0.6583449,0.0002876473,0.0005336353,0.0003609314,0.1018013,0.002244907,0.02018145,0.002358854,0.001206522,0.2083659],"study_design_scores_gemma":[0.002169111,0.000238377,0.9615474,0.00002347638,0.00006908256,0.00003644958,0.004952211,0.0008800377,0.009073031,0.001029602,0.01943383,0.0005474281],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9803613,0.00001879707,0.01007499,0.00005141149,0.0001282409,0.0003526285,0.000005433125,0.00004240693,0.00896476],"genre_scores_gemma":[0.9875852,0.00005816567,0.000906146,0.00005487012,0.00002046678,0.00008836677,0.0001575063,0.00001931568,0.01110989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3032024,"threshold_uncertainty_score":0.5792258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01595944607827089,"score_gpt":0.2103449173853539,"score_spread":0.194385471307083,"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."}}