{"id":"W2972333978","doi":"10.1016/j.jenvman.2019.109539","title":"Technical study on national mandatory guideline for deriving water quality criteria for the protection of freshwater aquatic organisms in China","year":2019,"lang":"en","type":"article","venue":"Journal of Environmental Management","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"Major Science and Technology Program for Water Pollution Control and Treatment; National Natural Science Foundation of China","keywords":"Water quality; China; Environmental planning; Environmental resource management; Quality (philosophy); Environmental science; Environmental quality; Pollutant; Business; Risk analysis (engineering); Environmental protection; Ecology; Geography; Biology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003039604,0.0001262283,0.0001991625,0.00007229314,0.00007588328,0.00002060083,0.000244068,0.00003703962,0.001188576],"category_scores_gemma":[0.00001457121,0.00007600603,0.0001072493,0.00004269186,0.00006091544,0.0001610427,0.0001594464,0.0001109841,0.00003741201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004538849,"about_ca_system_score_gemma":0.000003687017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002888657,"about_ca_topic_score_gemma":0.00004581789,"domain_scores_codex":[0.9980525,0.0001408401,0.0008394909,0.0001839337,0.0006078884,0.0001752849],"domain_scores_gemma":[0.999441,0.00005711338,0.0002896459,0.0001751699,0.000004284531,0.00003277017],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.002794576,0.01053391,0.07241527,0.0003384906,0.0005140469,0.00001160939,0.005460357,0.02801836,0.8592647,0.001016266,0.006977075,0.01265534],"study_design_scores_gemma":[0.005484637,0.002692279,0.9305758,0.00006820644,0.0001089358,0.000009017825,0.002506349,0.002477968,0.02587566,0.003404865,0.02647474,0.0003215564],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9707416,0.00000599703,0.02466593,0.001630016,0.000243381,0.002422058,0.00003023887,0.000004495852,0.0002562345],"genre_scores_gemma":[0.9949438,0.000004367047,0.004318524,0.0002830026,0.00004263155,0.00009087702,0.000006795771,0.00001244272,0.0002975481],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8581605,"threshold_uncertainty_score":0.9997244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03344377920838712,"score_gpt":0.3243061666054836,"score_spread":0.2908623873970965,"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."}}