{"id":"W4389053881","doi":"10.14710/jpl.2022.48814","title":"Penentuan Status Mutu Air Sungai Pekalongan Menggunakan Metode Indeks Pencemaran (IP) dan CCME","year":2022,"lang":"id","type":"article","venue":"Jurnal Pasir Laut","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Physics; Forestry; Environmental science; Humanities; Geography; Art","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":[],"category_scores_codex":[0.002130526,0.0008962788,0.0008845065,0.0003797425,0.00214418,0.0003021129,0.002762877,0.000339728,0.001737038],"category_scores_gemma":[0.0002415744,0.0009269777,0.0004317758,0.001190621,0.000976079,0.000800635,0.004314214,0.002757823,0.0007698375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002643096,"about_ca_system_score_gemma":0.0002009421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003013486,"about_ca_topic_score_gemma":0.0003427309,"domain_scores_codex":[0.9909357,0.001211835,0.001246953,0.001570078,0.002790429,0.002244982],"domain_scores_gemma":[0.9965346,0.0002680264,0.0007203131,0.001783311,0.00004122872,0.0006524775],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008183259,0.003779377,0.7328722,0.0003929039,0.0008930782,0.002359455,0.02476103,0.007560208,0.1665758,0.002760549,0.02813846,0.02908853],"study_design_scores_gemma":[0.001987677,0.001684301,0.7030227,0.0001050565,0.0002337228,0.0002250553,0.01113545,0.0004560189,0.0485896,0.001858106,0.2287198,0.001982579],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9869573,0.0005487783,0.00004584254,0.005068431,0.002636753,0.0008425365,0.0002434967,0.0006625868,0.00299426],"genre_scores_gemma":[0.9924212,0.0002256426,0.0007507584,0.000395709,0.000402228,0.0001737598,0.00006206315,0.0001358934,0.005432737],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2005813,"threshold_uncertainty_score":0.9995428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02765177308391657,"score_gpt":0.2597879492201771,"score_spread":0.2321361761362606,"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."}}