{"id":"W7067881260","doi":"","title":"Municipal solid waste supply chain mapping analysis","year":2018,"lang":"en","type":"other","venue":"NPARC","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Municipal solid waste; Supply chain; Greenhouse gas; Waste treatment; Waste collection; Production (economics); Waste disposal","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0005567624,0.0005784354,0.0003576777,0.002048086,0.0004241244,0.001022835,0.0003928177,0.0005581075,0.004144968],"category_scores_gemma":[0.001331524,0.0002555377,0.0008033851,0.002693126,0.0001886843,0.001262741,0.0005389847,0.0003067632,0.0004827039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001143055,"about_ca_system_score_gemma":0.00169426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01976713,"about_ca_topic_score_gemma":0.0139245,"domain_scores_codex":[0.9996608,0.0001034428,0.000013653,0.00005305463,0.0001224277,0.00004657605],"domain_scores_gemma":[0.9996349,0.0001402828,0.00005466701,0.00004426107,0.0001118574,0.00001401848],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00008070198,0.00008573812,0.01584726,0.0001101417,0.00007428434,0.0001397147,0.000105013,0.8978316,0.001890846,0.008633026,0.001647489,0.07355432],"study_design_scores_gemma":[0.000004393269,0.00002098233,0.003179263,0.00001460714,0.00002005217,0.00003159211,0.0001572103,0.9874876,0.002093811,0.005045589,0.001936084,0.000008918588],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.724361,0.0004633056,0.2461079,0.000525235,0.00003048683,0.0001848278,0.003066573,0.001009035,0.02425167],"genre_scores_gemma":[0.9514624,0.0003042862,0.04122358,0.00001502323,0.000006630893,0.00005196229,0.001273333,0.00006228568,0.005600553],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01976713,"threshold_uncertainty_score":0.03930414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03748519868427082,"score_gpt":0.2219369021029878,"score_spread":0.184451703418717,"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."}}