{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004557362,0.0001477291,0.00018157,0.001122911,0.0003196138,0.0004486409,0.0001927103,0.0001986517,0.0004495198],"category_scores_gemma":[0.000650499,0.0001003355,0.0002197677,0.002132036,0.000332262,0.0004849907,0.0005260968,0.0001894302,0.0000748977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009297676,"about_ca_system_score_gemma":0.0006323463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05924236,"about_ca_topic_score_gemma":0.09488506,"domain_scores_codex":[0.9997798,0.0000289947,0.00002932999,0.00006551464,0.0000499273,0.00004642641],"domain_scores_gemma":[0.9994346,0.00003661723,0.0001922241,0.00003005045,0.0002144114,0.0000920055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002439622,0.00001292279,0.9925142,0.00002287119,0.00003227314,0.0001005126,0.0007553875,0.0001522392,0.0006977869,0.00006524739,0.0001578166,0.005464265],"study_design_scores_gemma":[3.277076e-7,0.00001036349,0.9989731,0.000003042809,0.000004159875,0.00002234676,0.0004437662,0.000138346,0.00004410536,0.000009943113,0.0003488476,0.000001687162],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988845,0.0001572999,0.00007161814,0.00004441357,0.000002303558,0.000005350751,0.0003707241,0.000003215158,0.0004606436],"genre_scores_gemma":[0.9988874,0.0001666279,0.00008849962,0.00001170746,0.000003294912,0.000006748358,0.0004761856,0.000001543177,0.0003580682],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05924236,"threshold_uncertainty_score":0.1177951,"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."}}