{"id":"W7021014382","doi":"","title":"
\\nKAJIAN STATUS MUTU AIR SUNGAI 
\\nMENGGUNAKAN METODE CANADIAN COUNCIL OF MINISTERS OF THE ENVIRONMENT – WATER QUALITY INDEX (CCME-WQI) DAN OREGON WATER QUALITY INDEX (OWQI)
\\n
\\n
\\nStudi Kasus : Sungai Klampok, Kabupaten Semarang
\\n","year":2019,"lang":"id","type":"dissertation","venue":"UNDIP Institutional Repository (UNDIP-IR) (Diponegoro University)","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hydrology (agriculture); Box–Jenkins; Air quality index; Water quality","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","sts","research_integrity"],"category_scores_codex":[0.005371274,0.002993558,0.003409168,0.001577958,0.004661574,0.0003727947,0.004087869,0.002627054,0.001755465],"category_scores_gemma":[0.0002433256,0.002568026,0.002174728,0.001439014,0.00633159,0.002351961,0.001815601,0.002947396,0.0006894229],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.02227642,"about_ca_system_score_gemma":0.007587864,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6091265,"about_ca_topic_score_gemma":0.5583213,"domain_scores_codex":[0.9748594,0.005313101,0.004505726,0.003952362,0.007506215,0.003863182],"domain_scores_gemma":[0.9889643,0.0006570827,0.003301378,0.003890521,0.0008964497,0.002290277],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006393974,0.00463221,0.7801595,0.00333937,0.005545044,0.0008950703,0.04957744,0.05773142,0.08422053,0.00615376,0.0006878132,0.0006638617],"study_design_scores_gemma":[0.006375058,0.0007135702,0.8520376,0.0007661754,0.001642008,0.00009844273,0.01482679,0.0005112638,0.0381163,0.000304044,0.08087251,0.003736204],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9470916,0.0003357703,0.0005150284,0.001253816,0.005354966,0.003727032,0.002579631,0.0001735137,0.03896862],"genre_scores_gemma":[0.9355917,0.0002661781,0.0000639647,0.0004893635,0.0002885125,0.00006271191,0.003723895,0.0002100018,0.05930368],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0801847,"threshold_uncertainty_score":0.9993529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02696140250030564,"score_gpt":0.2307223236894933,"score_spread":0.2037609211891877,"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."}}