{"id":"W4386031912","doi":"10.2166/wpt.2023.129","title":"Transformation products of contaminants of emerging concern in water by UV-based processes","year":2023,"lang":"en","type":"article","venue":"Water Practice & Technology","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agencia Estatal de Investigación; Ministerio de Ciencia, Innovación y Universidades; Canadian Institute for Advanced Research","keywords":"Photodegradation; Photocatalysis; Environmental chemistry; Chemistry; Pollutant; Effluent; Photodissociation; Contamination; Photochemistry; Degradation (telecommunications); Orbitrap; Environmental science; Mass spectrometry; Chromatography; Environmental engineering; Organic chemistry; Catalysis; Computer science; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002257941,0.0003330841,0.0001471453,0.000347345,0.0002088204,0.0004052606,0.0001660456,0.0003350054,0.001377102],"category_scores_gemma":[0.0003378591,0.0001175752,0.0002535743,0.0003060822,0.0002260584,0.0003434841,0.000297679,0.0003238617,0.0003407038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000313351,"about_ca_system_score_gemma":0.0002843408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001116989,"about_ca_topic_score_gemma":0.001632222,"domain_scores_codex":[0.9996808,0.00004663413,0.00001352804,0.00008984157,0.0001190728,0.00005014457],"domain_scores_gemma":[0.9998816,0.00002237719,0.00003838342,0.000007273144,0.00004416977,0.000006144785],"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":[0.0001059779,0.0000206842,0.0021888,0.0001723102,0.00001926389,0.0001429051,0.00006138604,0.0002448329,0.985246,0.0001496615,0.0001358694,0.01151239],"study_design_scores_gemma":[0.000002498125,0.00008950502,0.002674548,0.00001527738,0.00001322714,0.0001294548,0.00007231628,0.0005164783,0.9937567,0.00008120014,0.002643747,0.000005002478],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9801717,0.002901474,0.01185784,0.00009895667,0.00002830887,0.00007021309,0.0006440569,0.0001055989,0.004121935],"genre_scores_gemma":[0.9875415,0.001791565,0.007183632,0.00008888775,0.000007836536,0.00003885581,0.0003244459,0.00002987167,0.002993347],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001377102,"threshold_uncertainty_score":0.004606903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02263187856773066,"score_gpt":0.2957465859379269,"score_spread":0.2731147073701962,"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."}}