{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001590995,0.00009785068,0.00009328527,0.00001953921,0.0003103343,0.00004386251,0.00006127588,0.00004704987,0.00003708047],"category_scores_gemma":[0.00008998412,0.00009794801,0.00002111104,0.0001765064,0.00003779315,0.00007984145,0.0001099186,0.00006660551,0.00001213512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001387828,"about_ca_system_score_gemma":0.000005803132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000320097,"about_ca_topic_score_gemma":0.0002749127,"domain_scores_codex":[0.9991772,0.00002859505,0.000134883,0.000301312,0.0002038421,0.0001542297],"domain_scores_gemma":[0.9996846,0.0000391479,0.00005758393,0.00009371169,0.00001209609,0.000112906],"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":[0.0002356193,0.00006510093,0.02443193,0.00003288879,0.000007247379,0.00000173894,0.0004050465,0.9634036,0.001972434,0.00002976043,0.003280308,0.006134266],"study_design_scores_gemma":[0.0007062057,0.0002502496,0.001992245,0.000008506468,0.00002617692,4.041586e-7,0.00003123526,0.9935654,0.001516211,0.00001586608,0.001786155,0.000101362],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4806045,0.00002147595,0.5169345,0.0009810358,0.0001117788,0.0009277567,0.00006765781,0.00004799271,0.0003033379],"genre_scores_gemma":[0.9983593,0.00003437256,0.0009561346,0.0003726809,0.00005726634,0.0000260525,0.0001184848,0.000009495631,0.00006623869],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5177548,"threshold_uncertainty_score":0.3994204,"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."}}