{"id":"W2079919908","doi":"10.3141/1791-09","title":"Planning and Design of Flex-Route Transit Services","year":2002,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"FLEX; Dwell time; Operator (biology); Transit (satellite); Computer science; Operations research; Service (business); Transport engineering; Industrial engineering; Mathematical optimization; Simulation; Engineering; Public transport; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006433149,0.0007789243,0.0004942967,0.0007898957,0.0006150045,0.001455886,0.0009036603,0.0008613471,0.003984606],"category_scores_gemma":[0.001316847,0.0006321269,0.0005231246,0.0007274117,0.0008140795,0.0009501555,0.0007731373,0.0005298043,0.0005130855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001705704,"about_ca_system_score_gemma":0.003184838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009487604,"about_ca_topic_score_gemma":0.01258285,"domain_scores_codex":[0.9992924,0.0002526721,0.00002299264,0.0001056566,0.0001562288,0.00017008],"domain_scores_gemma":[0.9996661,0.0001038956,0.00005510737,0.00001800007,0.00007650413,0.00008041409],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003666431,0.00001379143,0.0002131655,0.00003638179,0.000006778024,0.0001183158,0.00005198372,0.9754295,0.0009714407,0.01171973,0.0004676166,0.01093451],"study_design_scores_gemma":[0.000008275279,0.0000359718,0.0001037352,0.000009448098,0.000005318779,0.00003323194,0.00009978806,0.9910825,0.0004623707,0.005850187,0.002302109,0.00000713369],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0967328,0.000895393,0.8664708,0.0007086209,0.00005539756,0.0004527633,0.0003593297,0.0005372156,0.0337877],"genre_scores_gemma":[0.8269737,0.001002782,0.1634834,0.00005843075,0.00001995998,0.0002811032,0.0002732256,0.00009754133,0.007809792],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009487604,"threshold_uncertainty_score":0.01886475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1291833002273009,"score_gpt":0.3544997052228237,"score_spread":0.2253164049955228,"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."}}