{"id":"W2615318020","doi":"10.3808/jei.201600353","title":"Probabilistic Evaluation of Causal Relationship between Variables for Water Quality Management","year":2016,"lang":"en","type":"article","venue":"Journal of Environmental Informatics","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; University of Calgary","keywords":"Multivariate statistics; Probabilistic logic; Joint probability distribution; Variable (mathematics); Context (archaeology); Marginal distribution; Econometrics; Conditional probability distribution; Variables; Causality (physics); Statistics; Computer science; Multivariate normal distribution; Data mining; Random variable; Mathematics; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.008168776,0.0006045486,0.0007275881,0.002452251,0.0004259863,0.001552522,0.0009258135,0.0008727849,0.001923923],"category_scores_gemma":[0.02816604,0.0004440575,0.001060419,0.001853144,0.001005034,0.00243776,0.001471539,0.001178326,0.0001330314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001063497,"about_ca_system_score_gemma":0.001478152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005064876,"about_ca_topic_score_gemma":0.00456438,"domain_scores_codex":[0.9963185,0.002311633,0.0001741686,0.0004363733,0.0006257487,0.0001336018],"domain_scores_gemma":[0.9810402,0.01677921,0.0009995735,0.0004364199,0.0005797271,0.000164919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001723478,0.000117381,0.01495815,0.0002162021,0.000164623,0.0001669682,0.0002776262,0.8321856,0.001818013,0.06990763,0.0004650086,0.07955047],"study_design_scores_gemma":[0.000005838302,0.00003513728,0.002049942,0.00001588131,0.00002621426,0.00003021525,0.00004428487,0.9698183,0.0003381558,0.02725847,0.0003614542,0.00001612427],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03660399,0.0003072491,0.9618437,0.0002383257,0.00001275299,0.00005201439,0.0001355908,0.0001330186,0.0006733286],"genre_scores_gemma":[0.8146448,0.0005226996,0.1835446,0.00006184323,0.00005237672,0.0001597611,0.000362969,0.00004383887,0.0006070995],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008168776,"threshold_uncertainty_score":0.04320109,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1043757445224147,"score_gpt":0.338945559622955,"score_spread":0.2345698151005403,"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."}}