{"id":"W3038826406","doi":"10.22630/pniks.2020.29.2.14","title":"Assessment of Lower Zab river water quality using both Canadian Water Quality Index Method and NSF Water Quality Index Method","year":2020,"lang":"en","type":"article","venue":"Scientific Review Engineering and Environmental Sciences (SREES)","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Water quality; Turbidity; Environmental science; Raw water; Hydrology (agriculture); Alkalinity; Index (typography); Biochemical oxygen demand; Environmental engineering; Salinity; Surface water; Chemical oxygen demand; Wastewater; Engineering; Ecology; Chemistry","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":[0.0005640198,0.0005491404,0.0005929809,0.003894713,0.001217655,0.000928887,0.0006862669,0.00037251,0.001741718],"category_scores_gemma":[0.0006261313,0.0001931538,0.0006191505,0.006841516,0.0003714395,0.0004455997,0.0008941291,0.0004230439,0.0002496149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003554309,"about_ca_system_score_gemma":0.006656283,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6795473,"about_ca_topic_score_gemma":0.8070405,"domain_scores_codex":[0.9979001,0.00007762305,0.00008876081,0.0002367027,0.001533099,0.0001636274],"domain_scores_gemma":[0.9993376,0.00002005686,0.00007592096,0.00001855232,0.0005142515,0.00003363114],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003249123,0.0002235547,0.636103,0.001045852,0.0002846895,0.0005312982,0.001714757,0.00659299,0.1043416,0.001837456,0.006620988,0.2403789],"study_design_scores_gemma":[0.00002467388,0.0001180868,0.943941,0.00008771267,0.0001175796,0.0002312528,0.001254604,0.01625624,0.01718434,0.0004031052,0.02026164,0.0001197962],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9190407,0.001663691,0.03348436,0.0003861813,0.00005911754,0.0008127136,0.01221647,0.0004462016,0.03189047],"genre_scores_gemma":[0.918964,0.001391774,0.05704595,0.000124264,0.0000130757,0.0004963866,0.00882183,0.0000454643,0.01309721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6795473,"threshold_uncertainty_score":0.6446798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05123813644827795,"score_gpt":0.3418703999521793,"score_spread":0.2906322635039014,"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."}}