{"id":"W2161310124","doi":"10.1139/s07-050","title":"A field-based procedure for determining number of waste sorts for solid waste characterization","year":2008,"lang":"en","type":"article","venue":"Journal of Environmental Engineering and Science","topic":"Municipal Solid Waste Management","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Field (mathematics); Municipal solid waste; Computer science; Sampling (signal processing); Standard deviation; Statistics; Software; Characterization (materials science); Process engineering; Data mining; Waste management; Mathematics; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0003426951,0.0001088842,0.0001692925,0.00006268056,0.0001290254,0.0000148517,0.0002076007,0.00003047437,0.00003977071],"category_scores_gemma":[0.00006817878,0.00009775459,0.00006418044,0.0001040774,0.0001604432,0.0003036539,0.00008481327,0.00006190538,9.372071e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008042972,"about_ca_system_score_gemma":0.00001417576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001259108,"about_ca_topic_score_gemma":2.543848e-7,"domain_scores_codex":[0.9989843,0.000004862764,0.0003137514,0.0001625422,0.0003128493,0.0002216899],"domain_scores_gemma":[0.9995027,0.00005473413,0.0002256747,0.0001064277,0.000006130671,0.0001043569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001127395,0.0001419562,0.01584576,0.0001240236,0.00001645551,0.000008390152,0.0008448504,0.3515919,0.6276134,0.00002251543,0.00005660601,0.003621394],"study_design_scores_gemma":[0.001045935,0.0006806535,0.01687592,0.0001151845,0.00003408159,0.0001215664,0.0002062489,0.8602304,0.1195412,0.00001868633,0.0008825419,0.0002475696],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9696194,0.000009887298,0.02994312,0.00004367881,0.0001124001,0.0002127542,0.000007194998,0.000003611615,0.00004794052],"genre_scores_gemma":[0.9923787,0.00002007305,0.007389643,0.00006031979,0.00004711068,0.00001187391,0.00000127368,0.00001096763,0.00008005556],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5086384,"threshold_uncertainty_score":0.3986316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008756497869838873,"score_gpt":0.2213821326947413,"score_spread":0.2126256348249024,"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."}}