{"id":"W1549544518","doi":"10.1002/atr.1296","title":"A revised branch‐and‐price algorithm for dial‐a‐ride problems with the consideration of time‐dependent travel cost","year":2014,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Value of time; Travel time; Computer science; Arrival time; Service (business); Task (project management); Window (computing); Operations research; Level of service; Construct (python library); Transport engineering; Simulation; Real-time computing; Engineering; Economics; Computer network","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003209919,0.0001099566,0.0002238815,0.00008065447,0.00005690248,0.00001402364,0.00005403457,0.00004079756,0.00000921533],"category_scores_gemma":[0.00001718387,0.00008086473,0.00005751346,0.0001501225,0.00004310853,0.0002831401,2.486411e-7,0.0001197846,3.583868e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001924884,"about_ca_system_score_gemma":0.0000338944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002372116,"about_ca_topic_score_gemma":0.00006443608,"domain_scores_codex":[0.9990507,0.00001590737,0.0005546643,0.00008262155,0.0001939082,0.0001021517],"domain_scores_gemma":[0.9990432,0.0001600831,0.0002750507,0.00008293372,0.0003960751,0.00004267609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001829213,0.00008571298,0.0004851809,0.0003656597,0.0001703827,0.000001674897,0.004293001,0.7753656,0.1103064,0.001530888,0.00008495768,0.1071276],"study_design_scores_gemma":[0.0273265,0.002697305,0.7304655,0.001387645,0.001269376,0.0001170853,0.002781223,0.07108635,0.1442881,0.005065084,0.01215223,0.001363587],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2196555,0.0000823658,0.7792736,0.0002560774,0.00008993685,0.0005355403,0.0000479054,0.00001919446,0.0000398607],"genre_scores_gemma":[0.981921,0.0001089001,0.0177201,0.00005527488,0.00005150127,0.0000435345,0.00005944149,0.00002012819,0.0000201662],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7622654,"threshold_uncertainty_score":0.3297568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006874684862293479,"score_gpt":0.2146692647133824,"score_spread":0.2077945798510889,"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."}}