{"id":"W4411250482","doi":"10.7745/kjssf.2025.58.2.240","title":"Evaluation of long-term water quality trends and CCME-WQI applicability in agricultural watersheds of Korea","year":2025,"lang":"en","type":"article","venue":"Korean Journal of Soil Science and Fertilizer","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Rural Development Administration","keywords":"Term (time); Agriculture; Water quality; Environmental science; Water resource management; Geography; Archaeology; Ecology","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":[],"consensus_categories":[],"category_scores_codex":[0.008345386,0.0001014507,0.0002576562,0.0001525299,0.00007940504,0.00002910243,0.0002197754,0.0000459514,0.0001411289],"category_scores_gemma":[0.00006659981,0.00005708513,0.00005113287,0.0004573888,0.00112326,0.0004645199,0.0001468542,0.0001048427,0.000001036542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001811461,"about_ca_system_score_gemma":0.00005914049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002979007,"about_ca_topic_score_gemma":0.0002360717,"domain_scores_codex":[0.9976728,0.0002416979,0.0006389514,0.0002076219,0.001033219,0.0002057143],"domain_scores_gemma":[0.9993618,0.00003265969,0.000195385,0.0001488592,0.0001646488,0.0000966089],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001356723,0.0002585893,0.735041,0.00005152961,0.00001621574,0.000001067609,0.003965046,0.0002236602,0.1366942,0.0001188577,0.00003240008,0.1234618],"study_design_scores_gemma":[0.0007091744,0.00007709635,0.9070029,0.00004243947,0.00003847938,0.000006247808,0.0002955925,0.000212561,0.09026492,0.001274208,0.000009863171,0.00006648943],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964009,0.00006889801,0.0000441323,0.0008652341,0.00006048148,0.00008929386,0.000003043647,0.000002101001,0.002465936],"genre_scores_gemma":[0.9997757,0.00001906475,0.00007629568,0.00004499316,0.000007498961,0.000002609279,0.000001085632,0.000001521983,0.00007124044],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.171962,"threshold_uncertainty_score":0.41387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03709112328662147,"score_gpt":0.3303649862180889,"score_spread":0.2932738629314674,"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."}}