{"id":"W2955448449","doi":"10.1155/2019/5745870","title":"Limited-Stop High-Frequency Service Design: Reducing In-Vehicle Congestion","year":2019,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Service (business); Computer science; Transport engineering; Level of service; Work (physics); Travel time; Operations research; Engineering; Business; Marketing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005336364,0.0009770069,0.000775251,0.0005289828,0.0004166937,0.0006110552,0.001462985,0.0007998099,0.003196037],"category_scores_gemma":[0.001691951,0.0003709955,0.0004968989,0.0005456525,0.000538541,0.0008575108,0.0006435077,0.0004707724,0.0005228611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006780063,"about_ca_system_score_gemma":0.0009352828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004203307,"about_ca_topic_score_gemma":0.005233291,"domain_scores_codex":[0.9994617,0.0002166086,0.00001493636,0.00007938623,0.0001036786,0.0001237069],"domain_scores_gemma":[0.9993062,0.0002255646,0.0001154444,0.00005778313,0.0001683736,0.0001267131],"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":[0.0004963086,0.0002993448,0.002466852,0.0001398456,0.00006391495,0.00009949789,0.00009932535,0.9148397,0.00837524,0.003532033,0.001915502,0.06767249],"study_design_scores_gemma":[0.00004910392,0.0003337753,0.000707839,0.000006481936,0.00002396185,0.00005059182,0.00004804288,0.9946226,0.001676498,0.001748337,0.0007246829,0.000008107207],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3433403,0.0003545409,0.6489686,0.0002709017,0.00005070287,0.0001611036,0.0001978937,0.0007129391,0.005943026],"genre_scores_gemma":[0.9540486,0.00007487198,0.04405905,0.00005367746,0.00001751032,0.0000662612,0.0001563869,0.00004807057,0.001475501],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004203307,"threshold_uncertainty_score":0.01069176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01725740699863076,"score_gpt":0.2737974178544619,"score_spread":0.2565400108558312,"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."}}