{"id":"W4410250007","doi":"10.28991/hef-2025-06-01-015","title":"Global Trends in Agricultural Waste-Based Bioplastic Research: A Scientometric Review","year":2025,"lang":"en","type":"review","venue":"Journal of Human Earth and Future","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bioplastic; Agriculture; Environmental science; Engineering; Waste management; Biology; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["bibliometrics"],"domain":null,"study_design":"observational","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics"],"domain":null,"study_design":"design_other","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001167176,0.0002617204,0.0009744893,0.001157609,0.0001691512,0.00008108277,0.0003383999,0.0001969196,0.0007848252],"category_scores_gemma":[0.0001662348,0.0001576494,0.0002840119,0.005617606,0.0001570159,0.00009427587,0.000118512,0.0006888288,0.00002167591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002106364,"about_ca_system_score_gemma":0.0001293513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001336769,"about_ca_topic_score_gemma":0.0001253174,"domain_scores_codex":[0.9976568,0.0002941439,0.0007216648,0.000269472,0.0006770787,0.0003808405],"domain_scores_gemma":[0.9989772,0.0001812873,0.0004376146,0.0001430943,0.00004033265,0.0002204481],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000863197,0.00008761382,0.000110048,0.00864983,0.00002351424,0.00007941027,0.0000108769,0.00001714831,0.000002208076,0.00008539211,0.0209307,0.9699946],"study_design_scores_gemma":[0.0003319832,0.0002691083,0.003305347,0.02942314,0.0002501438,0.0001685241,0.00001403557,0.00000607217,2.150963e-7,0.00002111453,0.9660122,0.0001980969],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000232118,0.9966477,0.00001000195,0.00008137641,0.0004552563,0.0001706346,0.00007636806,0.000003157409,0.00232337],"genre_scores_gemma":[0.0003148563,0.9986681,0.00009169164,0.00004092063,0.0004205524,0.000002785965,0.00002562765,0.0000055205,0.000429908],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9697965,"threshold_uncertainty_score":0.8593285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04905072602789765,"score_gpt":0.3530761393913413,"score_spread":0.3040254133634437,"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."}}