{"id":"W4411243773","doi":"10.3390/su17125422","title":"Updating Water Quality Standards Criteria Considering Chemical Mixtures in the Context of Climate Change","year":2025,"lang":"en","type":"article","venue":"Sustainability","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Climate change; Context (archaeology); Environmental science; Quality (philosophy); Water quality; Environmental resource management; Biochemical engineering; Environmental economics; Engineering; Geology; Economics; Ecology; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004188412,0.000110493,0.0002058328,0.00002566996,0.00009773998,0.00003202489,0.0002135481,0.00006355425,0.0005770176],"category_scores_gemma":[0.0004624987,0.00006993119,0.0000627929,0.0001482846,0.0003833795,0.0001476188,0.0003055807,0.0001526031,0.000003222134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007442455,"about_ca_system_score_gemma":0.00004401244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002365213,"about_ca_topic_score_gemma":0.0002715158,"domain_scores_codex":[0.9980198,0.0006528727,0.0004507434,0.0002512456,0.0002851957,0.0003401882],"domain_scores_gemma":[0.9993451,0.0001543468,0.00005993536,0.0003541802,0.00005795493,0.00002846807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005268447,0.0008286779,0.7842178,0.002007157,0.00002991581,0.00001791711,0.08751784,0.00003277317,0.02832914,0.05776212,0.001412003,0.03731778],"study_design_scores_gemma":[0.001666206,0.00008813201,0.6642168,0.00009701592,0.00003109525,0.000002984187,0.04594303,0.0001826295,0.1707403,0.090831,0.02570777,0.0004930429],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9859647,0.0000198995,0.00009216989,0.009985811,0.00006820702,0.0004781376,0.00005061028,0.00001790378,0.003322612],"genre_scores_gemma":[0.9988022,0.000005177094,0.0001027278,0.000988332,0.00001284808,0.00006123417,0.000007451733,0.000003013773,0.00001695059],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1424112,"threshold_uncertainty_score":0.6317939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0261418731599148,"score_gpt":0.3637998026566822,"score_spread":0.3376579294967674,"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."}}