{"id":"W2036985034","doi":"10.1139/s06-005","title":"Residence time distribution analysis of an intermittently operating truck fill facility to determine effective contact time","year":2006,"lang":"en","type":"article","venue":"Journal of Environmental Engineering and Science","topic":"Water Systems and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Environmental Protection Agency","keywords":"Truck; Residence time distribution; Residence time (fluid dynamics); Environmental science; Residence; Schedule; Transport engineering; Environmental engineering; Flow (mathematics); Waste management; Engineering; Computer science; Automotive engineering; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003756583,0.00009463973,0.0002219853,0.0001773237,0.00004240556,0.0000421605,0.0001136638,0.00002507501,0.00001495702],"category_scores_gemma":[0.0000288304,0.00008237989,0.00004766243,0.0002777217,0.00003676394,0.0004144597,0.00002606701,0.00006550505,0.000002203392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000124046,"about_ca_system_score_gemma":0.000004547741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001416677,"about_ca_topic_score_gemma":0.000002218738,"domain_scores_codex":[0.9992307,0.00001310145,0.0003095513,0.0001134751,0.0002049902,0.0001281952],"domain_scores_gemma":[0.9997115,0.00002857794,0.00006498413,0.00009039412,0.00001595891,0.00008865303],"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":[0.000003525416,0.00001003229,0.001500193,0.000006837743,0.00001789943,0.00000327804,0.00008411925,0.6706693,0.3271109,9.233475e-7,0.000007890412,0.000585097],"study_design_scores_gemma":[0.0001038132,0.0001332957,0.2978292,0.0000352853,0.00004580904,0.00001979473,0.00001193704,0.6746114,0.02711272,5.512316e-7,0.00001603053,0.00008007018],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9822991,0.00004855958,0.01742725,0.000003239443,0.00005376144,0.00007171328,0.00006200896,0.00001148705,0.00002283843],"genre_scores_gemma":[0.998983,0.000002926773,0.0009413611,0.000001685012,0.00002183789,0.00000136431,0.000009634472,0.000004182054,0.00003400629],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2999982,"threshold_uncertainty_score":0.3359354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002434595817092998,"score_gpt":0.1680737050613774,"score_spread":0.1656391092442845,"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."}}