{"id":"W2112368500","doi":"10.3141/1994-12","title":"Development of a Fleet Allocator Model for Calgary, Canada","year":2007,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; BP (Canada)","funders":"","keywords":"Allocator; Fleet management; Transport engineering; Process (computing); Computer science; Engineering; Operations research; Automotive engineering; Simulation; Operating system","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":[0.0006912408,0.0009602367,0.0008988814,0.0009185129,0.001414595,0.001875305,0.002939398,0.001128496,0.005994673],"category_scores_gemma":[0.001561227,0.0007516075,0.0009097279,0.001787761,0.0006777007,0.000865223,0.0009308858,0.001297351,0.000975021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0134999,"about_ca_system_score_gemma":0.01970965,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9196005,"about_ca_topic_score_gemma":0.8587932,"domain_scores_codex":[0.9996096,0.00006162775,0.0000127466,0.00008135079,0.0001277881,0.0001068935],"domain_scores_gemma":[0.999481,0.0001037671,0.0000294937,0.00002120481,0.0003198211,0.00004470811],"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":[0.000008669184,0.000003820581,0.0003416971,0.000007651959,0.000004597544,0.00002900131,0.00001783035,0.991073,0.00006998257,0.004191806,0.001098674,0.003153312],"study_design_scores_gemma":[0.000003921769,0.000002431128,0.0001478918,0.0000039119,0.000002990532,0.000003724178,0.00001318071,0.997618,0.00003986654,0.0007657204,0.001393307,0.000005006165],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09747719,0.0008209651,0.8199472,0.001351191,0.0001637165,0.0005442405,0.006726663,0.001597241,0.07137166],"genre_scores_gemma":[0.7329158,0.001137311,0.1966781,0.0001942673,0.000043117,0.0007784666,0.005075374,0.0004228407,0.06275485],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08039945,"threshold_uncertainty_score":0.1617458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1146243959090826,"score_gpt":0.4067556330898566,"score_spread":0.2921312371807741,"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."}}