{"id":"W4213287388","doi":"10.1021/acs.est.1c06120","title":"Enhancing Scientific Support for the Stockholm Convention’s Implementation: An Analysis of Policy Needs for Scientific Evidence","year":2022,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; University of Toronto","funders":"RECETOX Přírodovědecké Fakulty Masarykovy Univerzity; Bundesamt für Umwelt; Miljødirektoratet; Environment and Climate Change Canada","keywords":"Convention; Political science; Government (linguistics); Work (physics); Civil society; Variety (cybernetics); Action (physics); Public administration; Public relations; Engineering ethics; Business; Law; Engineering; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":["sts"],"category_scores_codex":[0.002927165,0.0001645782,0.0002136758,0.001864415,0.003961519,0.0001431623,0.001327473,0.00004820839,0.004552307],"category_scores_gemma":[0.0001466416,0.0001455388,0.0001533328,0.007446,0.004397465,0.0004802639,0.000856718,0.0001256481,0.00002667167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001127671,"about_ca_system_score_gemma":0.0002025118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001166638,"about_ca_topic_score_gemma":0.0003233727,"domain_scores_codex":[0.9972546,0.00004050391,0.0004550632,0.0007618432,0.0008455329,0.00064251],"domain_scores_gemma":[0.998659,0.0002069507,0.000327797,0.0006812631,0.00001569795,0.0001093454],"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":[0.00003495667,0.000164023,0.01346411,0.000004415276,0.00004681613,4.276563e-7,0.001103686,0.01512405,0.9553908,0.005633443,0.0003043943,0.00872893],"study_design_scores_gemma":[0.001900561,0.003520495,0.1023836,0.00001455404,0.001692864,0.00005698789,0.03584727,0.1462798,0.5258082,0.004092474,0.177207,0.00119617],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9414929,0.00005584437,0.05525098,0.000665909,0.0006489838,0.001089152,0.0007215685,0.00003711612,0.00003759864],"genre_scores_gemma":[0.9970086,0.000004088214,0.001349279,0.00006760751,0.00002192383,0.0004200154,0.0001442742,0.00001128946,0.0009729748],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4295826,"threshold_uncertainty_score":0.998312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01736239668864817,"score_gpt":0.2883051890423055,"score_spread":0.2709427923536573,"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."}}