{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006222414,0.00009639978,0.0001933682,0.0002204747,0.00009708849,0.000026318,0.0001239371,0.0001047509,0.00008636318],"category_scores_gemma":[0.00005296065,0.0001019329,0.00004991844,0.0006330558,0.00002502554,0.001148961,3.873005e-7,0.0002078086,0.00001141123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001066551,"about_ca_system_score_gemma":0.0002117703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004353245,"about_ca_topic_score_gemma":0.0009317796,"domain_scores_codex":[0.998597,0.0001136191,0.0005613897,0.0001411054,0.0004031631,0.0001836676],"domain_scores_gemma":[0.9987656,0.0001417619,0.0004668225,0.00007768606,0.0004657316,0.00008235747],"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":[0.0001918528,0.00005526955,0.03052687,0.00002747373,0.00001074893,0.00001821619,0.02295192,0.9338026,0.007062017,0.002494411,0.00000953624,0.002849079],"study_design_scores_gemma":[0.002242219,0.0001934411,0.9857134,0.0004005536,0.00005149108,0.000002143275,0.007635135,0.0003745897,0.0009398618,0.001765758,0.0004556466,0.000225728],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.988556,0.0001255037,0.008921036,0.001166391,0.0006998866,0.0002391613,0.000004594799,0.00003371789,0.000253722],"genre_scores_gemma":[0.974292,0.0002338182,0.02513845,0.0001184935,0.00008568115,0.000003348271,0.00003893242,0.00001298977,0.00007627801],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9551865,"threshold_uncertainty_score":0.4156703,"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."}}