{"id":"W2931884396","doi":"10.1016/j.scitotenv.2019.03.372","title":"Comparison of regulatory frameworks of environmental risk assessments for human pharmaceuticals in EU, USA, and Canada","year":2019,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":62,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Health Canada; Government of Canada","keywords":"Legislation; Business; Human health; European union; Risk analysis (engineering); Environmental planning; Product (mathematics); Risk assessment; Environmental protection; Environmental resource management; Environmental health; Medicine; Geography; Environmental science; Political science; Economics; International trade","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.04451847,0.0008219551,0.001102865,0.01053439,0.005178342,0.01257278,0.006277694,0.003523829,0.002461863],"category_scores_gemma":[0.05038214,0.0008334995,0.003688074,0.006752485,0.005049912,0.001441024,0.003477259,0.003781831,0.000183057],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09648073,"about_ca_system_score_gemma":0.1747598,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9460961,"about_ca_topic_score_gemma":0.9606205,"domain_scores_codex":[0.9470788,0.01030268,0.001778692,0.001689872,0.03278507,0.006365004],"domain_scores_gemma":[0.9229165,0.02515256,0.002815268,0.001656323,0.04515073,0.002308572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00112579,0.0003069316,0.0373132,0.001608738,0.001303782,0.0005694465,0.004942683,0.1292278,0.004158679,0.6430333,0.06383684,0.1125729],"study_design_scores_gemma":[0.0006182204,0.0007870168,0.3579004,0.009065678,0.004211746,0.0003998686,0.01343558,0.05683983,0.01005022,0.08234286,0.4631218,0.001226741],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.2900453,0.02570365,0.02750313,0.04149259,0.0007431659,0.001546863,0.008350644,0.000594592,0.6040201],"genre_scores_gemma":[0.9472456,0.006251448,0.01946914,0.01046372,0.0001294543,0.0004563007,0.002086414,0.0001558791,0.01374216],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.9035193,"threshold_uncertainty_score":0.70002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02449057246739544,"score_gpt":0.3298752915588987,"score_spread":0.3053847190915033,"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."}}