{"id":"W4281492663","doi":"10.1007/978-981-19-0968-9_38","title":"Developing a Gis-Based Fleet Optimization Model for Winter Maintenance Operations","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in civil engineering","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Truck; Snow removal; Snow; Software deployment; Transport engineering; Environmental science; Geographic information system; Service (business); Computer science; Meteorology; Engineering; Geography; Business; Automotive engineering; Remote sensing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003939406,0.0008783504,0.0009782223,0.0005581492,0.0006638232,0.001145076,0.001445776,0.001612773,0.006908486],"category_scores_gemma":[0.0007921401,0.0009879105,0.001195849,0.0008415467,0.0004133277,0.0009281258,0.000713162,0.001018107,0.0008082522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001341831,"about_ca_system_score_gemma":0.001822226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06943623,"about_ca_topic_score_gemma":0.0428054,"domain_scores_codex":[0.9998834,0.00003152868,0.000007283277,0.00002995224,0.00002419856,0.00002367549],"domain_scores_gemma":[0.9997197,0.0001590946,0.00002167537,0.00001353242,0.0000640459,0.00002195824],"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":[0.0000041895,0.000004933203,0.00005674702,0.000004000303,0.000003340339,0.000009551216,0.00000264175,0.998593,0.00006491556,0.000211674,0.00008836771,0.0009565217],"study_design_scores_gemma":[0.000001938879,0.000002475507,0.00002011908,8.274577e-7,0.000001285793,0.000001355201,0.000002254428,0.9996985,0.00003045354,0.0001592108,0.00008081787,8.721112e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1330655,0.0003442432,0.8368798,0.0004785006,0.0001156588,0.0002342916,0.001687738,0.002017779,0.02517651],"genre_scores_gemma":[0.8224626,0.0002995444,0.1603191,0.0001175622,0.00003650651,0.0004898189,0.001471123,0.0004040884,0.01439957],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06943623,"threshold_uncertainty_score":0.1380641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01261394338935108,"score_gpt":0.2070715874000817,"score_spread":0.1944576440107306,"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."}}