{"id":"W4286500602","doi":"10.3390/land11071117","title":"Riverine Plastic Pollution in Asia: Results from a Bibliometric Assessment","year":2022,"lang":"en","type":"article","venue":"Land","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Yorkville University","funders":"European Commission","keywords":"Microplastics; Livelihood; Plastic pollution; Pollution; Scope (computer science); Environmental science; Pollutant; Environmental planning; Plastic waste; Environmental resource management; Environmental protection; Geography; Agriculture; Ecology; Computer science; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.004857712,0.0005576464,0.001217696,0.1016773,0.001054292,0.004987324,0.0005904203,0.0005369073,0.003516763],"category_scores_gemma":[0.01891022,0.0001914934,0.001456276,0.1845905,0.0008231461,0.002845915,0.002781627,0.0004078112,0.0007802983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002522269,"about_ca_system_score_gemma":0.004388489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01391759,"about_ca_topic_score_gemma":0.01337651,"domain_scores_codex":[0.9938158,0.0008326721,0.001796419,0.0005825719,0.002682766,0.0002897758],"domain_scores_gemma":[0.9749067,0.0116535,0.004872183,0.0009561983,0.007019337,0.0005920276],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002754573,0.0002024214,0.5436013,0.0298616,0.002240025,0.001187386,0.01116661,0.002219184,0.001412716,0.007057005,0.02826216,0.3725141],"study_design_scores_gemma":[0.00002050547,0.00009490873,0.8959073,0.004224307,0.001962435,0.0008096375,0.01299057,0.002114227,0.00094987,0.002034304,0.07878405,0.0001078082],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7543011,0.07404346,0.002950724,0.003929095,0.0002117811,0.000414792,0.1001358,0.0004971685,0.06351613],"genre_scores_gemma":[0.8768798,0.06323007,0.00552978,0.0002524509,0.0002184593,0.0003435199,0.05041761,0.00008257743,0.003045743],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8983228,"threshold_uncertainty_score":0.02767318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01040191255386546,"score_gpt":0.2266409415045498,"score_spread":0.2162390289506843,"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."}}