{"id":"W4401916531","doi":"10.3390/w16172413","title":"Analysis of the Water Quality Status and Its Historical Evolution Trend in the Mainstream and Major Tributaries of the Yellow River Basin","year":2024,"lang":"en","type":"article","venue":"Water","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Tributary; Water quality; Environmental science; Hydrology (agriculture); Water resources; Water resource management; Geography; Geology; Ecology; Cartography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006762439,0.00007739344,0.0001409529,0.00003910516,0.00008198592,0.00002226335,0.0001218312,0.00004199265,0.0002463868],"category_scores_gemma":[0.000008346619,0.00002468821,0.00008247126,0.0002262519,0.0002619209,0.00009773007,0.0001564359,0.00009151029,0.000005702665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000205685,"about_ca_system_score_gemma":0.000005251978,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003808463,"about_ca_topic_score_gemma":0.003102808,"domain_scores_codex":[0.9987845,0.0004081528,0.0002307573,0.0001570743,0.0002507867,0.0001686991],"domain_scores_gemma":[0.9997142,0.00004511355,0.00002870626,0.0001863127,0.000003347541,0.00002231924],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000803998,0.0002055632,0.8861284,0.0001155391,0.0002930593,0.0000026101,0.07506931,0.0005872718,0.03319182,0.001568752,0.001396308,0.00136096],"study_design_scores_gemma":[0.0001940226,0.00002167646,0.9554062,0.00001163607,0.000230404,0.000001432545,0.0002764283,0.0006405074,0.01917266,0.001039504,0.02292647,0.0000790624],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9932656,0.00006287842,0.00001841133,0.00624074,0.00008400658,0.0001091867,0.00006176178,0.000004028588,0.0001533613],"genre_scores_gemma":[0.998458,0.00000909634,0.00001202931,0.00009351844,0.000007397753,0.000005258971,0.000006806901,0.000002568028,0.001405284],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07479288,"threshold_uncertainty_score":0.5757283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01877079102456135,"score_gpt":0.2554780421636705,"score_spread":0.2367072511391092,"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."}}