{"id":"W2728395416","doi":"10.1177/1687814017706433","title":"Vehicle routing and scheduling of demand-responsive connector with on-demand stations","year":2017,"lang":"en","type":"article","venue":"Advances in Mechanical Engineering","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Fundamental Research Funds for the Central Universities; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Routing (electronic design automation); Scheduling (production processes); Computer science; Transit (satellite); On demand; Public transport; Demand management; Transport engineering; Operations research; Computer network; Engineering; Operations management; Economics","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":[0.0004544632,0.0007296052,0.0005746465,0.0003735924,0.0006016733,0.0008392668,0.001147586,0.0006996085,0.003147423],"category_scores_gemma":[0.0007522423,0.0004260438,0.0004728576,0.0006589746,0.0003317935,0.0005838692,0.0005552335,0.0003846117,0.0002474067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001586047,"about_ca_system_score_gemma":0.001485824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02141992,"about_ca_topic_score_gemma":0.0180581,"domain_scores_codex":[0.9996135,0.0001123017,0.00001142267,0.00007028103,0.00005468264,0.0001378794],"domain_scores_gemma":[0.9997312,0.00006968738,0.00004731348,0.00002256678,0.00006056266,0.00006865607],"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":[0.00008856157,0.0000533769,0.001016231,0.00002874863,0.00001405248,0.0001186312,0.00003413695,0.9815158,0.002660506,0.003475317,0.001079104,0.009915631],"study_design_scores_gemma":[0.000007056443,0.00003336601,0.0002357797,7.165902e-7,0.000004220081,0.000009769117,0.00003306139,0.9983116,0.0004150224,0.0006098779,0.0003357693,0.000003713144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4974952,0.0001859245,0.4852399,0.0003684374,0.0001132268,0.0002727952,0.0004213464,0.0006331144,0.01527013],"genre_scores_gemma":[0.9737638,0.00007464766,0.02239677,0.00002214254,0.0000100833,0.00005325475,0.0002719884,0.00004720008,0.003360085],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02141992,"threshold_uncertainty_score":0.0425905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008058166270838127,"score_gpt":0.2491272821381033,"score_spread":0.2410691158672652,"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."}}