{"id":"W2141452637","doi":"10.5555/2675983.2676355","title":"Utilizing simulation derived quantitative formulas for accurate excavator Hauler fleet selection","year":2013,"lang":"en","type":"article","venue":"Winter Simulation Conference","topic":"BIM and Construction Integration","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Natural Resources; University of Alberta","funders":"","keywords":"Excavator; Earthworks; Granularity; Computer science; Selection (genetic algorithm); Discrete event simulation; Field (mathematics); Production (economics); Duration (music); Industrial engineering; Operations research; Engineering; Simulation; Civil engineering; Artificial intelligence; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007830507,0.0002147481,0.000180117,0.000148187,0.0001410643,0.0002060637,0.00009398756,0.0001394817,0.000668515],"category_scores_gemma":[0.00009633108,0.0002152888,0.00008225426,0.0001786053,0.00003425095,0.00116736,0.00001247989,0.0001301088,0.0001484447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009009772,"about_ca_system_score_gemma":0.00002851841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000161249,"about_ca_topic_score_gemma":0.00004180709,"domain_scores_codex":[0.9989419,0.00003243677,0.0003996255,0.0002476734,0.0001406812,0.0002376987],"domain_scores_gemma":[0.9987714,0.0002503184,0.00009824039,0.0001355219,0.0006762506,0.00006825203],"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":[0.00003412071,0.00001042909,0.0003020181,0.0000368857,0.00004351504,8.490208e-8,0.0006072386,0.9496596,0.01383775,0.005696968,0.0001958167,0.02957553],"study_design_scores_gemma":[0.0004619926,0.00006271873,0.002696113,0.00004653337,0.00001741249,0.000001209298,0.0003064405,0.9846722,0.006607801,0.002536624,0.002347944,0.0002430461],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2715206,0.00002080451,0.7257558,0.00005187937,0.0004917994,0.0005594603,0.00001018301,0.0003280223,0.001261478],"genre_scores_gemma":[0.9943716,0.000003723292,0.005022258,0.00006426767,0.0001125288,0.0001711585,0.00005910297,0.00003339443,0.0001619926],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7228509,"threshold_uncertainty_score":0.8779224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05505243749383319,"score_gpt":0.2997921766228763,"score_spread":0.2447397391290431,"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."}}