{"id":"W4229813510","doi":"10.1109/wsc.2017.8248049","title":"Data-driven simulation-based model for planning roadway operation and maintenance projects","year":2017,"lang":"en","type":"article","venue":"2017 Winter Simulation Conference (WSC)","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Truck; Snow removal; Snow; Computer science; Operational planning; Resource (disambiguation); Data modeling; Operations research; Transport engineering; Real-time computing; Simulation; Engineering; Automotive engineering; Meteorology; Database","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006390029,0.0009893738,0.001057472,0.0009018501,0.0007550968,0.001502314,0.002078682,0.001698169,0.006530133],"category_scores_gemma":[0.0013911,0.00085891,0.001238583,0.001131059,0.0006874079,0.0009082604,0.0008846949,0.001136741,0.0006038916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002589922,"about_ca_system_score_gemma":0.0031079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08898003,"about_ca_topic_score_gemma":0.06938786,"domain_scores_codex":[0.9997088,0.00009022687,0.00001997435,0.00004843726,0.0000780349,0.00005440632],"domain_scores_gemma":[0.9993356,0.0003446538,0.00005834644,0.00003067741,0.0001515841,0.00007911443],"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":[0.000009909296,0.000008078628,0.0001498736,0.000006507737,0.000004517336,0.00001149455,0.000005832625,0.9985024,0.0000586443,0.0007879771,0.00007577435,0.0003790394],"study_design_scores_gemma":[0.000006052952,0.000003855339,0.00003652852,0.000002085683,0.000002490602,0.000001656454,0.000005696002,0.9992732,0.00005024627,0.0003762938,0.0002396635,0.00000222913],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1767963,0.0005523699,0.7611239,0.001040561,0.0002109524,0.0005473442,0.006349873,0.002140853,0.05123796],"genre_scores_gemma":[0.9096571,0.0005150707,0.07319352,0.000132093,0.00003378817,0.00107593,0.00311918,0.0001680064,0.01210522],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08898003,"threshold_uncertainty_score":0.1769242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.143616142391013,"score_gpt":0.3498062278500631,"score_spread":0.2061900854590501,"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."}}