{"id":"W3151074763","doi":"10.36278/jeaht.24.1.13","title":"Assessment of Water Quality and Sediment Pollution in Gap Stream","year":2021,"lang":"en","type":"article","venue":"Journal of Environmental Analysis Health and Toxicology","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Environmental Research; Ministry of Environment","keywords":"Tributary; Environmental science; Pollution; Sediment; Hydrology (agriculture); Water quality; Nutrient; Organic matter; Bank; Surface water; Sampling (signal processing); Environmental engineering; Ecology; Geology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006722877,0.00009481852,0.0004336585,0.0001190633,0.0000546247,0.000006567444,0.00005289605,0.00006020418,0.0002374838],"category_scores_gemma":[0.000006875965,0.00006905608,0.00008848734,0.0001482492,0.0001580992,0.00009686065,0.0001252557,0.0001360654,0.000001285071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002819249,"about_ca_system_score_gemma":0.00002314325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001169749,"about_ca_topic_score_gemma":0.0001194884,"domain_scores_codex":[0.9984434,0.0002528895,0.0006681782,0.000181435,0.0002382627,0.0002157872],"domain_scores_gemma":[0.9993712,0.0000321195,0.000294921,0.00009529165,0.000003059021,0.0002033645],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002838933,0.0004385074,0.9911952,0.00001511149,0.00009922971,0.00001641194,0.000286708,0.0009964326,0.003950888,0.00003678697,0.00001077819,0.002925535],"study_design_scores_gemma":[0.0007209511,0.0004057046,0.9956622,0.000005877705,0.00008717167,0.00003431308,0.0004991891,0.0009573154,0.0004736425,0.0008397882,0.000244681,0.00006921152],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970865,0.0003416837,0.0001585001,0.002176182,0.00004384399,0.00005175751,0.00001138882,0.0000010327,0.0001291144],"genre_scores_gemma":[0.997109,0.001252459,0.0007162755,0.0008604566,0.00001256678,0.000001234042,0.00001404161,0.000003269151,0.0000306803],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004466933,"threshold_uncertainty_score":0.2816026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01724979274223524,"score_gpt":0.3047697082230739,"score_spread":0.2875199154808387,"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."}}