{"id":"W3150657358","doi":"10.1051/e3sconf/202124701024","title":"Waste recycling: share in the structure of the tariff for the treatment of solid municipal waste in the Vologda region","year":2021,"lang":"en","type":"article","venue":"E3S Web of Conferences","topic":"Transportation Systems and Logistics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Incineration; Municipal solid waste; Tariff; Russian federation; Business; Population; Waste disposal; Waste management; Environmental protection; Geography; Engineering; Environmental health; International trade; Economic policy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001402493,0.00009665343,0.0002161524,0.00002645979,0.00003263812,0.00001016482,0.0003357343,0.00006537893,0.00001857322],"category_scores_gemma":[0.00003483845,0.00003935862,0.00008407146,0.0001667401,0.00008307584,0.00002100688,0.000005409296,0.00009365271,6.686909e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008363522,"about_ca_system_score_gemma":0.0001103643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003283312,"about_ca_topic_score_gemma":0.01035457,"domain_scores_codex":[0.9992161,0.0000878555,0.0003599556,0.00008288233,0.0001494228,0.0001037283],"domain_scores_gemma":[0.9990391,0.0004529036,0.0001176938,0.0003155421,0.00006781249,0.000006934173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002827948,0.0005931854,0.1449379,0.001482297,0.0007688581,0.000038706,0.2646928,0.4362402,0.02277146,0.1062768,0.00151156,0.02040341],"study_design_scores_gemma":[0.00563148,0.001177432,0.2704619,0.001642767,0.0005329777,0.00003503328,0.4271803,0.1153062,0.1028359,0.009068266,0.06540731,0.000720415],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967873,0.001120634,0.0001901171,0.0004764684,0.0002385822,0.0003884512,0.0001699945,0.000005006193,0.0006234969],"genre_scores_gemma":[0.9995586,0.0002688666,0.00003147216,0.00001634493,0.00004662992,0.00001938339,0.00001578754,0.000005079884,0.00003789595],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3209341,"threshold_uncertainty_score":0.5778094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05325149044948398,"score_gpt":0.272116843634181,"score_spread":0.218865353184697,"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."}}