{"id":"W2977045589","doi":"","title":"PENENTUAN STATUS MUTU DAN STRATEGI PENGENDALIAN PENCEMARAN AIR SUNGAI SEBAGAI UPAYA PENGELOLAAN KUALITAS LINGKUNGAN(Studi Kasus: Sungai Rambut, Kabupaten Pemalang-Tegal, Jawa Tengah)","year":2019,"lang":"id","type":"dissertation","venue":"","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Physics; Forestry; Environmental science; Geography","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":[0.002031664,0.0004574413,0.0003333595,0.0006866997,0.00207355,0.005552921,0.0005753387,0.0009883073,0.02893965],"category_scores_gemma":[0.003324209,0.0002105064,0.0005170398,0.0005315783,0.001408239,0.003374116,0.002529017,0.001372217,0.003364682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002645155,"about_ca_system_score_gemma":0.004566083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005305674,"about_ca_topic_score_gemma":0.008861726,"domain_scores_codex":[0.9987106,0.0003939841,0.00005649714,0.0002168092,0.0002819445,0.0003400847],"domain_scores_gemma":[0.9975351,0.0008880119,0.0003762299,0.0001868262,0.000427179,0.0005866373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0009366766,0.001786796,0.2486248,0.002028501,0.000300294,0.001706276,0.1129626,0.002402507,0.009892239,0.2490981,0.0239648,0.3462964],"study_design_scores_gemma":[0.0001235105,0.001300069,0.3677067,0.001337066,0.0004378156,0.0007473584,0.2376662,0.002944448,0.00722457,0.0772623,0.3030263,0.0002237077],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6123083,0.001244199,0.005548989,0.00503817,0.0002347871,0.0002566772,0.0005655701,0.00008528747,0.374718],"genre_scores_gemma":[0.9517967,0.0006767382,0.002006486,0.0003613038,0.00001921037,0.000145771,0.0001922797,0.00002782552,0.0447736],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02893965,"threshold_uncertainty_score":0.09681273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03397325015831426,"score_gpt":0.2922112693711897,"score_spread":0.2582380192128755,"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."}}