{"id":"W2620349118","doi":"10.1002/ieam.1949","title":"Towards a proportionality assessment of risk reduction measures aimed at restricting the use of persistent and bioaccumulative substances","year":2017,"lang":"en","type":"article","venue":"Integrated Environmental Assessment and Management","topic":"Toxic Organic Pollutants Impact","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Eidgenössische Anstalt für Wasserversorgung Abwasserreinigung und Gewässerschutz; Rijksinstituut voor Volksgezondheid en Milieu; National Ethnic Affairs Commission of the People's Republic of China","keywords":"Proportionality (law); Bioaccumulation; Benchmarking; Risk analysis (engineering); Legislation; Hazardous waste; Environmental science; Environmental economics; Business; Economics; Engineering; Waste management; Chemistry; Environmental chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006356784,0.0002376706,0.0002566606,0.00004720429,0.0005987856,0.00008410394,0.000254962,0.00005768561,0.0002853927],"category_scores_gemma":[0.00003193769,0.0001598067,0.0001039259,0.00007854494,0.001106806,0.0004560915,0.0006359432,0.0001681494,0.000001947528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006907747,"about_ca_system_score_gemma":0.00001434947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009739411,"about_ca_topic_score_gemma":0.0001590682,"domain_scores_codex":[0.9980327,0.0001722102,0.0004430515,0.00042504,0.0006882623,0.0002387365],"domain_scores_gemma":[0.9985727,0.00005320487,0.0007722698,0.0005075844,0.000003232876,0.00009100512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001174942,0.0004072992,0.709367,0.00002890795,0.000640397,0.000008035626,0.0009061423,0.0007758582,0.02174981,0.0002479337,0.0001674152,0.2655837],"study_design_scores_gemma":[0.0005351019,0.0001449178,0.9904959,0.0000417062,0.0002434401,0.000008167925,0.001899386,0.003121594,0.002400301,0.0001552983,0.0007850939,0.000169096],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966633,0.0001016677,0.0005065835,0.0003500695,0.0001069735,0.0006757004,0.0001661091,0.00001477471,0.001414774],"genre_scores_gemma":[0.9932739,0.00176454,0.004656675,0.00001493217,0.00001071934,0.00002239876,0.000009295579,0.00001425597,0.0002332422],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2811289,"threshold_uncertainty_score":0.6516728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0530557772340929,"score_gpt":0.3030919244918183,"score_spread":0.2500361472577254,"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."}}