{"id":"W4406227063","doi":"10.1016/j.trpro.2024.12.091","title":"Data Driven Synchronization Strategies of a Bus Line in a Transit Network","year":2025,"lang":"en","type":"article","venue":"Transportation research procedia","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Polytechnique Montréal","keywords":"Transit (satellite); Line (geometry); Synchronization (alternating current); Computer science; Bus rapid transit; Transport engineering; Computer network; Real-time computing; Public transport; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001625113,0.00008813407,0.0001738765,0.0003502109,0.0002427619,0.00005544029,0.0004203652,0.0001396588,0.00006131343],"category_scores_gemma":[0.0001599757,0.00009777825,0.00002424516,0.002500795,0.000258767,0.0006351823,0.000003626587,0.0002557025,0.000003666662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005006235,"about_ca_system_score_gemma":0.001425448,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00287903,"about_ca_topic_score_gemma":0.1118109,"domain_scores_codex":[0.9980577,0.0001849457,0.0004598631,0.00031889,0.0006184336,0.0003602017],"domain_scores_gemma":[0.9988594,0.0002223932,0.00007880421,0.0002258376,0.0005505001,0.00006307238],"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":[0.000208024,0.0002587558,0.1135027,0.0005447332,0.0000476677,0.00001676605,0.03910499,0.5977824,0.0001002167,0.2407121,0.002044861,0.005676854],"study_design_scores_gemma":[0.002797649,0.0001827361,0.8418626,0.001340637,0.00008763705,1.184125e-7,0.06510802,0.06361045,0.0001182459,0.0124064,0.0120605,0.0004250153],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5592045,0.001783579,0.4088471,0.005407941,0.0005204905,0.003659316,0.0006673015,0.0006558264,0.01925394],"genre_scores_gemma":[0.9949625,0.0005707696,0.002972427,0.00002221044,0.00006612585,0.00004482005,0.001118512,0.00001236671,0.0002303377],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7283599,"threshold_uncertainty_score":0.9043962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09164851402244263,"score_gpt":0.4301667841043678,"score_spread":0.3385182700819252,"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."}}