{"id":"W3039812688","doi":"10.5276/jswtm/2019.441","title":"Carbon Footprint of Municipal Solid Waste Management in Guelph City, Ontario","year":2019,"lang":"en","type":"article","venue":"The Journal of Solid Waste Technology and Management","topic":"Municipal Solid Waste Management","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Greenhouse gas; Municipal solid waste; Carbon footprint; Waste management; Environmental science; Carbon dioxide equivalent; Life-cycle assessment; Environmental engineering; Ton; Waste treatment; Carbon dioxide; Landfill gas; Engineering; Production (economics)","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":[0.0001707278,0.0002943251,0.0002678924,0.0005486099,0.002060499,0.001070732,0.0005707671,0.0004160415,0.001510058],"category_scores_gemma":[0.0004477295,0.00022798,0.0003619372,0.001635105,0.0006333194,0.0002739538,0.0005969179,0.0002180584,0.0001514001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04603229,"about_ca_system_score_gemma":0.02830316,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9949301,"about_ca_topic_score_gemma":0.9982992,"domain_scores_codex":[0.9995191,0.00005528159,0.00001278506,0.00004641161,0.0002334994,0.000132898],"domain_scores_gemma":[0.999699,0.00002542854,0.00004021759,0.00001062401,0.000161865,0.00006299467],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001973284,0.0002845389,0.6558917,0.001456422,0.0005402587,0.004904106,0.006737435,0.1018401,0.06335966,0.007018814,0.03202694,0.1239668],"study_design_scores_gemma":[0.00008128135,0.0001914877,0.930629,0.00008829118,0.000116781,0.0001929947,0.006999458,0.02465802,0.005920624,0.0004380357,0.03059009,0.00009400931],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.984234,0.0004510222,0.0002706335,0.0005198497,0.00000808323,0.00007455833,0.002195152,0.00004703339,0.01219957],"genre_scores_gemma":[0.9917316,0.0003509064,0.0007399758,0.00006452636,0.000002172423,0.00002548653,0.0007307981,0.00001108369,0.006343525],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04603229,"threshold_uncertainty_score":0.3339892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01118472291916949,"score_gpt":0.2366411933223174,"score_spread":0.2254564704031479,"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."}}