{"id":"W630811522","doi":"","title":"Optimization of Winter Road Maintenance Under Traffic and Weather Information","year":2015,"lang":"en","type":"article","venue":"Transportation Research Board 94th Annual MeetingTransportation Research Board","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Truck; Flexibility (engineering); Transport engineering; Snow removal; Snow; Storm; Visibility; Environmental science; Meteorology; Computer science; Engineering; Geography; Automotive engineering; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006508023,0.0009855147,0.0009714368,0.0005833899,0.0004641157,0.001199514,0.0008139474,0.00122572,0.002380355],"category_scores_gemma":[0.001354527,0.0006692608,0.0008672176,0.0006315112,0.0005930191,0.0008060065,0.0007103518,0.0006437512,0.0002267773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001824689,"about_ca_system_score_gemma":0.001364648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03359405,"about_ca_topic_score_gemma":0.02383391,"domain_scores_codex":[0.9995769,0.000116815,0.00001321424,0.00006066961,0.00004602586,0.0001864279],"domain_scores_gemma":[0.9994867,0.0002642345,0.00009273476,0.0000233102,0.00005450785,0.00007862113],"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":[0.00003641818,0.00002041476,0.0003511576,0.00001085811,0.00001216086,0.00002728636,0.000008174199,0.9969656,0.0003894515,0.0003959644,0.0001474893,0.001635042],"study_design_scores_gemma":[0.00001352413,0.00006616621,0.0006218666,0.000002298836,0.00001133772,0.00001210332,0.00002768213,0.9982306,0.0002199581,0.0006342522,0.0001559048,0.000004253739],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7980836,0.0006430387,0.184949,0.0005268403,0.00005675852,0.0001308976,0.000748402,0.0003274093,0.01453396],"genre_scores_gemma":[0.9909592,0.000157136,0.005590214,0.00001934045,0.000007780533,0.00003257741,0.00018017,0.0000349342,0.003018785],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03359405,"threshold_uncertainty_score":0.06679702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03426663962622196,"score_gpt":0.3120881005603759,"score_spread":0.277821460934154,"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."}}