{"id":"W3045697690","doi":"10.31025/2611-4135/2020.13995","title":"A SPATIAL-AND-SCALE-DEPENDANT MODEL FOR PREDICTING MSW GENERATION, DIVERSION AND COLLECTION COST BASED ON DWELLING-TYPE DISTRIBUTION","year":2020,"lang":"en","type":"article","venue":"Detritus","topic":"Municipal Solid Waste Management","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Data collection; Scale (ratio); Predictive modelling; Economies of agglomeration; Statistics; Population; Duplex (building); Environmental science; Waste collection; Computer science; Mathematics; Municipal solid waste; Engineering; Geography; Cartography; Waste management","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007101735,0.001158006,0.0009132239,0.0009468271,0.0006576643,0.001230846,0.002297204,0.001599948,0.002158883],"category_scores_gemma":[0.001148077,0.0007923031,0.00117077,0.0009931674,0.000703262,0.0008298992,0.0006144494,0.001128483,0.0003307772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003031032,"about_ca_system_score_gemma":0.003095432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2308868,"about_ca_topic_score_gemma":0.1549721,"domain_scores_codex":[0.9997548,0.00004691882,0.00001149488,0.00007618756,0.00003888713,0.00007175578],"domain_scores_gemma":[0.9995285,0.0002208876,0.00006728381,0.00002333882,0.0001264619,0.00003351572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008715607,0.00001506346,0.001118545,0.000006984324,0.00001079017,0.00002342987,0.00001214369,0.9967154,0.0002745465,0.0005083667,0.00007841279,0.001227511],"study_design_scores_gemma":[0.000002080104,0.000007161684,0.0003954967,8.445849e-7,0.000004218135,0.000003065357,0.000005080235,0.9993005,0.00006884446,0.0001409566,0.00006841517,0.000003344934],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5586867,0.0003504315,0.426841,0.0004686506,0.0000815651,0.0003005061,0.003174925,0.001265435,0.00883064],"genre_scores_gemma":[0.9741709,0.0001811051,0.01741901,0.00003270877,0.00001496432,0.0002757163,0.0005955898,0.00004740246,0.007262585],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2308868,"threshold_uncertainty_score":0.4590857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03218324166026169,"score_gpt":0.2325945092513075,"score_spread":0.2004112675910458,"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."}}