{"id":"W2017971019","doi":"10.1021/es801611a","title":"Herbicidal Effects of Sulfamethoxazole in <i>Lemna gibba</i>: Using <i>p</i>-Aminobenzoic Acid As a Biomarker of Effect","year":2008,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":112,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Toronto; Natural Sciences and Engineering Research Council of Canada; Baylor University","keywords":"Lemna gibba; Dihydropteroate synthase; DHPS; Metabolite; Sulfamethoxazole; Chemistry; EC50; Lemna; Dinitrobenzene; Lomefloxacin; Sulfonamide; Potency; Mode of action; Biochemistry; Pharmacology; Antibiotics; Biology; Botany; Stereochemistry; Ciprofloxacin; Pyrimethamine; In vitro; Aquatic plant; Ofloxacin","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0005687388,0.0003391854,0.000517847,0.0004347606,0.0001945757,0.000005802494,0.0008404332,0.0002111851,0.0005858312],"category_scores_gemma":[0.0001449048,0.0002995389,0.0001160752,0.001820603,0.008592437,0.0004615528,0.001036594,0.0003113103,0.0001873866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004812601,"about_ca_system_score_gemma":0.00002825659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002422671,"about_ca_topic_score_gemma":0.000008491499,"domain_scores_codex":[0.9969814,0.0001082415,0.0005340186,0.000724147,0.0008089594,0.0008432402],"domain_scores_gemma":[0.9989005,0.0001138042,0.0002437032,0.0005148109,0.000001732253,0.0002254756],"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":[0.00003492835,0.0003871944,0.2523512,0.00002117499,0.000006092947,0.00007297735,0.0001090221,0.0001193074,0.740907,0.0000146215,0.000005759847,0.005970675],"study_design_scores_gemma":[0.0008346874,0.0004582321,0.2466566,0.00004532661,0.00001844797,0.0001655609,0.00005365852,0.0006146186,0.7506519,0.000166482,0.0001115397,0.0002229156],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971348,0.0003337027,0.0001250997,0.00007980029,0.0001226569,0.0005080263,0.000007010323,0.00003851951,0.001650401],"genre_scores_gemma":[0.9981128,0.0001397126,0.001529345,0.0001235287,0.00000683059,0.000008873385,0.000001651631,0.00002310831,0.00005412561],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009744898,"threshold_uncertainty_score":0.9999457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01245404186560402,"score_gpt":0.2709312653491243,"score_spread":0.2584772234835203,"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."}}