{"id":"W3094317533","doi":"10.1016/j.watres.2020.116542","title":"Nontargeted identification and predicted toxicity of new byproducts generated from UV treatment of water containing micropollutant 2-mercaptobenzothiazole","year":2020,"lang":"en","type":"article","venue":"Water Research","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":59,"is_retracted":false,"has_abstract":false,"ca_institutions":"Trojan Technologies (Canada); University of Alberta","funders":"Alberta Innovates; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Canada Research Chairs","keywords":"Toxicity; Chemistry; Environmental chemistry; Water treatment; Photodegradation; Water quality; Environmental engineering; Environmental science; Photocatalysis; Organic chemistry; Catalysis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001336503,0.0004599298,0.0001737607,0.0003124347,0.0001411795,0.0003209781,0.0002157191,0.0004619175,0.0006743605],"category_scores_gemma":[0.0002399656,0.000161159,0.0003689626,0.0001610561,0.0001613401,0.0001558191,0.0001629011,0.0002521891,0.0002688074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003809976,"about_ca_system_score_gemma":0.0002460113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001390859,"about_ca_topic_score_gemma":0.001617504,"domain_scores_codex":[0.9998568,0.0000109533,0.000005239888,0.0000429056,0.0000613673,0.00002262983],"domain_scores_gemma":[0.9998239,0.00003641213,0.00007358729,0.00001113536,0.00004165203,0.00001350336],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003369462,0.00003365111,0.008843007,0.00006944825,0.00002011698,0.0001292153,0.00002952679,0.002129713,0.9845769,0.00006950795,0.00005880998,0.003703188],"study_design_scores_gemma":[0.00000980562,0.0003843208,0.01910002,0.000004363194,0.00004300494,0.0001593566,0.00003832972,0.01764606,0.9622042,0.00007276706,0.0003297789,0.000008029337],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9940798,0.0002353362,0.005025088,0.0000159276,0.000004755632,0.00001807938,0.0002212232,0.00007640365,0.00032345],"genre_scores_gemma":[0.9962592,0.0002413594,0.00209307,0.0000155816,0.000002436993,0.00001669457,0.0003711636,0.00001203871,0.0009884515],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001390859,"threshold_uncertainty_score":0.002765536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09575577896658495,"score_gpt":0.3312921355415219,"score_spread":0.2355363565749369,"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."}}