{"id":"W4392821211","doi":"10.1016/j.tra.2024.104031","title":"A collective incentive strategy to manage ridership rebound and consumer surplus in mass transit systems","year":2024,"lang":"en","type":"article","venue":"Transportation Research Part A Policy and Practice","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Incentive; Economic surplus; Revenue; Price elasticity of demand; Microeconomics; Transit (satellite); Total revenue; Economics; Transit system; Business; Transport engineering; Public transport; Finance; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00328373,0.0001119421,0.0001600057,0.0005903198,0.0004825716,0.0004803045,0.00007153202,0.0001207241,0.00003557683],"category_scores_gemma":[0.0006261922,0.0001196543,0.00002050979,0.001741287,0.0002809743,0.0008953041,0.000001453973,0.0003600468,0.00001545889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001724225,"about_ca_system_score_gemma":0.0009538404,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03032667,"about_ca_topic_score_gemma":0.02151011,"domain_scores_codex":[0.9973022,0.00108675,0.0002843756,0.0003695256,0.0005496183,0.0004075005],"domain_scores_gemma":[0.9966032,0.002786939,0.00003977287,0.00007524112,0.0002631898,0.0002316524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001427134,0.0001020666,0.004532735,0.0005365631,0.0001539627,0.0003360139,0.460591,0.008718004,0.00008427207,0.5186713,0.00148572,0.003361192],"study_design_scores_gemma":[0.001594722,0.0005471982,0.06155428,0.000849831,0.0001419306,0.00000573722,0.1548994,0.002535037,0.00003349972,0.008657612,0.768545,0.000635709],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6524255,0.0110737,0.01770305,0.07025947,0.0008968356,0.007847386,0.00109435,0.0006380797,0.2380616],"genre_scores_gemma":[0.9905711,0.002022466,0.0002131767,0.0001226202,0.0001107689,0.0001226311,0.00005221539,0.00001499649,0.006770027],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7670593,"threshold_uncertainty_score":0.9963448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1574644095408083,"score_gpt":0.4670247070821425,"score_spread":0.3095602975413342,"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."}}