{"id":"W1994182583","doi":"10.1061/9780784412602.0197","title":"Evaluating Advanced Pickup and Delivery Systems: A Simulation Study","year":2012,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Pickup; Paratransit; Computer science; Simulation modeling; Set (abstract data type); Simulation; Systems engineering; Engineering; Transport engineering; Public transport; Artificial intelligence","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":[0.002286293,0.0008366614,0.000896393,0.0009108737,0.0008493626,0.001101916,0.001338767,0.001391434,0.002168116],"category_scores_gemma":[0.003971842,0.0004232434,0.0007323212,0.001347902,0.0007209731,0.001073896,0.0006770364,0.001148281,0.0001951738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003313169,"about_ca_system_score_gemma":0.002079017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05954842,"about_ca_topic_score_gemma":0.04482084,"domain_scores_codex":[0.9988881,0.0006384818,0.00003979377,0.00007464449,0.0002158055,0.0001432147],"domain_scores_gemma":[0.9949234,0.003761693,0.0002527055,0.0002415422,0.0006198082,0.0002008445],"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":[0.0001165363,0.0002838752,0.003790085,0.0000399917,0.00002081897,0.00009711226,0.0001077059,0.9894816,0.0005733398,0.002311845,0.0002182672,0.002958893],"study_design_scores_gemma":[0.00009895733,0.000489915,0.001522833,0.00001456981,0.00002279764,0.00002556677,0.0002448786,0.9948859,0.001093779,0.0005640974,0.00101868,0.00001804049],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9662317,0.0001983117,0.02170621,0.000282138,0.00002218108,0.0003454522,0.0004871028,0.0001141175,0.0106128],"genre_scores_gemma":[0.9863869,0.0002593277,0.0115717,0.00003219176,0.000007153188,0.0001633855,0.000281829,0.00001268745,0.001284743],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05954842,"threshold_uncertainty_score":0.1184037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06254696486744744,"score_gpt":0.3414217366933116,"score_spread":0.2788747718258642,"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."}}