{"id":"W4405800233","doi":"10.3390/toxics13010006","title":"Global Assessment of Emerging Contaminant Removal in Wastewater Treatment Plants: In Silico Hazard Screening and Risk Evaluation","year":2024,"lang":"en","type":"article","venue":"Toxics","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"ARC Resources (Canada)","funders":"Ministero dell’Istruzione, dell’Università e della Ricerca","keywords":"Bioaccumulation; Hazardous waste; Quantitative structure–activity relationship; Environmental science; Environmental impact of pharmaceuticals and personal care products; Environmental chemistry; Bioconcentration; Hazard analysis; Risk assessment; Wastewater; Aquatic environment; Hazard; Biochemical engineering; Chemistry; Computer science; Environmental engineering; Biology; Ecology; Engineering","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":[0.001345542,0.0007599736,0.0006163169,0.001224454,0.0001846394,0.0007617467,0.0004574579,0.0005990441,0.001108187],"category_scores_gemma":[0.001597497,0.000236259,0.001235085,0.00086438,0.0002051702,0.0003770688,0.000444786,0.0002557712,0.0002060178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009073547,"about_ca_system_score_gemma":0.000895849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005716197,"about_ca_topic_score_gemma":0.004515994,"domain_scores_codex":[0.9996921,0.0001430655,0.00001853138,0.00005162745,0.00006591612,0.00002876242],"domain_scores_gemma":[0.9990959,0.000634124,0.0001091114,0.00003906546,0.0001023657,0.00001946826],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001143805,0.0001214108,0.01417871,0.0002948519,0.0001660287,0.00009287283,0.00002628974,0.9651172,0.007645363,0.0003503417,0.0001297315,0.0117628],"study_design_scores_gemma":[0.00004046956,0.0006154366,0.008797346,0.0000213857,0.0001965433,0.00008827185,0.00007048324,0.9787274,0.009731388,0.0009292638,0.0007637692,0.00001829081],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9430434,0.001071383,0.04967036,0.0001499921,0.000006744689,0.0001301133,0.002341841,0.0003218959,0.00326424],"genre_scores_gemma":[0.9789848,0.0006572457,0.01747502,0.00003275862,0.000003342733,0.00009818737,0.002127819,0.00002209923,0.0005988432],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005716197,"threshold_uncertainty_score":0.01136589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03381573491650469,"score_gpt":0.3492475843839855,"score_spread":0.3154318494674808,"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."}}