{"id":"W2188369615","doi":"","title":"Evaluation Water Quality Index for Irrigation in the North of Hilla city by Using the Canadian and Bhargava Methods","year":2014,"lang":"en","type":"article","venue":"Journal of University of Babylon for Pure and Applied Sciences","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Irrigation; Environmental science; Water quality; Hydrology (agriculture); Water resource management; Geology; Agronomy; Ecology; Biology","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":[0.0006051401,0.0003564621,0.0003472576,0.003090463,0.0008472832,0.00103593,0.0004945257,0.0001965378,0.001921169],"category_scores_gemma":[0.001301156,0.0001187735,0.000542672,0.005554327,0.0004018986,0.0003347528,0.0007760485,0.0003539732,0.0001917907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00452684,"about_ca_system_score_gemma":0.004745625,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5573835,"about_ca_topic_score_gemma":0.7508378,"domain_scores_codex":[0.9987836,0.0001158019,0.00006168714,0.0001136273,0.0007941697,0.0001310959],"domain_scores_gemma":[0.9989138,0.000109308,0.0001417418,0.0000334845,0.0007402204,0.00006150555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003922344,0.000220096,0.7296703,0.0006169073,0.0003584753,0.0003523923,0.00288097,0.008345991,0.0146068,0.003895716,0.005926771,0.2327332],"study_design_scores_gemma":[0.00002173404,0.0001721638,0.961671,0.00006895875,0.0001065493,0.0001425781,0.003357811,0.01747546,0.005341632,0.0005863344,0.01097661,0.0000792219],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9368716,0.0008924149,0.01649624,0.0002847654,0.0000511594,0.0004069526,0.003823226,0.0001835798,0.04099008],"genre_scores_gemma":[0.9701515,0.0004875429,0.0196268,0.00003332536,0.000006161251,0.0001903755,0.001719491,0.00002173966,0.007763064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5573835,"threshold_uncertainty_score":0.8904462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07598632897663123,"score_gpt":0.3332483123359791,"score_spread":0.2572619833593479,"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."}}