{"id":"W2974148870","doi":"10.1126/science.aax3539","title":"Cleaning up plastic pollution in Africa","year":2019,"lang":"en","type":"article","venue":"Science","topic":"Recycling and Waste Management Techniques","field":"Environmental Science","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Plastic pollution; Pollution; Key (lock); Environmental science; Environmental planning; Business; Environmental protection; Environmental resource management; Natural resource economics; Computer science; Ecology; Computer security; Economics; Biology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000594267,0.00004983545,0.00004908644,0.00008324207,0.0000681513,0.0000394819,0.0003170827,0.00001536702,0.00029157],"category_scores_gemma":[0.00006059561,0.00004399044,0.00001157578,0.0007344527,0.000191493,0.0003229114,0.0002085856,0.00006109295,0.001079654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000127257,"about_ca_system_score_gemma":0.000006863081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005404056,"about_ca_topic_score_gemma":0.00001158122,"domain_scores_codex":[0.9990852,0.00001149975,0.00008678155,0.0002595407,0.0003026188,0.0002543962],"domain_scores_gemma":[0.9997512,0.00001800912,0.00002764043,0.0001649376,0.000002073017,0.00003620796],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002390121,0.00009916615,0.6671728,0.00001711088,0.000001635996,0.000008729059,0.002178798,0.02212841,0.1913821,0.004005915,0.00351246,0.1094689],"study_design_scores_gemma":[0.0002328908,0.0001135553,0.9385429,0.00005426164,0.000002102108,0.000002015695,0.0003899666,0.02863867,0.006660971,0.002977613,0.02213747,0.0002475901],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.894081,0.000005825639,0.0006984075,0.00009059167,0.0002731585,0.000101781,1.767641e-7,0.00006309026,0.104686],"genre_scores_gemma":[0.9972029,0.000003667489,0.0007768052,0.00006287159,0.000005854133,0.000002978368,1.107691e-7,0.000002773628,0.001941997],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2713701,"threshold_uncertainty_score":0.9996981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01053091435570856,"score_gpt":0.2252361888905638,"score_spread":0.2147052745348553,"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."}}