{"id":"W3204491645","doi":"10.34218/ijciet.12.8.2021.005","title":"SURFACE WATER QUALITY ASSESSMENT AND MAPPING OF PERIYAR RIVER USING CANADIAN COUNCIL OF MINISTERS OF THE ENVIRONMENT WATER QUALITY INDEX METHOD","year":2021,"lang":"en","type":"article","venue":"INTERNATIONAL JOURNAL OF CIVIL ENGINEERING AND TECHNOLOGY (IJCIET)","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Water quality; Index (typography); Council of Ministers; Surface water; Environmental science; Quality (philosophy); Hydrology (agriculture); Water resource management; Environmental engineering; Computer science; Business; Engineering; Geotechnical engineering; 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":[0.0009000612,0.0005815601,0.0004559044,0.005122358,0.001077929,0.001217879,0.0007978943,0.0002986604,0.002055883],"category_scores_gemma":[0.001415888,0.0002107783,0.0006002906,0.009905647,0.000310253,0.0004687314,0.001016783,0.000432526,0.0003925135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003203065,"about_ca_system_score_gemma":0.01133796,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6681694,"about_ca_topic_score_gemma":0.723475,"domain_scores_codex":[0.9978749,0.00009932168,0.0001205104,0.000275716,0.001395471,0.0002341025],"domain_scores_gemma":[0.9984518,0.0000450931,0.0001077667,0.0000516382,0.001286786,0.00005687574],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002220011,0.0002609847,0.4618092,0.001145115,0.0002227081,0.0007812558,0.001960324,0.02489818,0.02706629,0.004378851,0.03847343,0.4387817],"study_design_scores_gemma":[0.0000321345,0.00005390932,0.8827628,0.0001201575,0.00007819769,0.0001566927,0.002179621,0.0604357,0.008104766,0.0006918157,0.0452623,0.0001219411],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7073671,0.00189362,0.1389667,0.001019328,0.0001557966,0.001872169,0.04937227,0.002496595,0.09685643],"genre_scores_gemma":[0.8528819,0.001130126,0.1054465,0.0001142158,0.00001814273,0.001007151,0.02113298,0.0001445264,0.01812445],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6681694,"threshold_uncertainty_score":0.6675695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04069957393530407,"score_gpt":0.2881277146001041,"score_spread":0.2474281406648,"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."}}