{"id":"W6940705730","doi":"10.1021/acs.est.3c04348.s004","title":"A\\nCity-Wide Emissions Inventory of Plastic Pollution","year":2024,"lang":"en","type":"dataset","venue":"Figshare","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Plastic pollution; Pollution; Greenhouse gas; Baseline (sea); Air pollution; Reduction (mathematics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004059435,0.0008714238,0.0004695607,0.001724861,0.0004955704,0.0008933038,0.001233919,0.0008316879,0.00854444],"category_scores_gemma":[0.001462675,0.0003938832,0.001016321,0.004019188,0.0002564738,0.0005376998,0.000977206,0.000725873,0.006331126],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002641605,"about_ca_system_score_gemma":0.002694036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3400404,"about_ca_topic_score_gemma":0.4641075,"domain_scores_codex":[0.9997252,0.00003796743,0.00002651414,0.00008123932,0.00007657398,0.00005247561],"domain_scores_gemma":[0.999359,0.00008321337,0.0001034837,0.000118886,0.000264723,0.00007069059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001810849,0.00006707349,0.04746988,0.001897644,0.0003059201,0.0001722208,0.0001512475,0.01209886,0.0010995,0.003032837,0.9217165,0.01180714],"study_design_scores_gemma":[0.0001508301,0.00002577759,0.09223187,0.0003390906,0.00009055818,0.0001012597,0.0002638276,0.007329661,0.00126737,0.001213522,0.8969319,0.00005426311],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001971931,0.0001324836,0.0002320335,0.00009904155,0.00001385249,0.000009739495,0.9961172,0.0001403801,0.001283324],"genre_scores_gemma":[0.004842498,0.0001579617,0.0006992813,0.00004166007,0.000005449443,0.00004550352,0.9932743,0.00002502308,0.000908224],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3400404,"threshold_uncertainty_score":0.6761222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02759609339288226,"score_gpt":0.2363406437079884,"score_spread":0.2087445503151061,"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."}}