{"id":"W2955775098","doi":"10.1016/j.envsci.2019.06.005","title":"Plastics at sea: Treaty design for a global solution to marine plastic pollution","year":2019,"lang":"en","type":"article","venue":"Environmental Science & Policy","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":163,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Treaty; Enforcement; Negotiation; Business; Corporate governance; Scope (computer science); Environmental governance; Liability; Environmental planning; International trade; Environmental resource management; Political science; Environmental science; Law; Accounting; Finance; Computer science","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004160547,0.0003058976,0.0002167277,0.0001149924,0.000594506,0.00006753803,0.0004597981,0.000100048,0.001873949],"category_scores_gemma":[0.0002613656,0.0002890365,0.00008415511,0.000695718,0.0006022282,0.0003316485,0.000857714,0.00008446354,0.005064437],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005084402,"about_ca_system_score_gemma":0.0001007236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006145767,"about_ca_topic_score_gemma":0.0001824171,"domain_scores_codex":[0.9971001,0.0000398093,0.0003109995,0.0007986693,0.0007337597,0.001016698],"domain_scores_gemma":[0.9988678,0.0001390921,0.0001235115,0.0003378324,0.000004194726,0.0005275623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0006428169,0.0004130122,0.1326875,0.0000161588,0.0000191339,0.000005236898,0.000383718,0.116774,0.7221202,0.002214132,0.004794402,0.01992967],"study_design_scores_gemma":[0.001511222,0.001207764,0.8831728,0.0000215182,0.00004747103,0.00007422012,0.00004876111,0.08059858,0.01508951,0.001165745,0.01630405,0.0007584404],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.904896,0.000005991381,0.0896776,0.0003362868,0.0005716566,0.0009905761,0.0003449114,0.00005051646,0.003126524],"genre_scores_gemma":[0.9915576,0.000009143097,0.006385099,0.0003638675,0.0001410469,0.00004604011,0.00003378711,0.0000191904,0.001444245],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7504852,"threshold_uncertainty_score":0.9999562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009284737718876026,"score_gpt":0.2269073640457341,"score_spread":0.2176226263268581,"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."}}