{"id":"W4400183149","doi":"10.2139/ssrn.4881689","title":"Subway-Emergency Bridging Strategy for Bus-Scheduling Considering Passenger Travel Behavior","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Bridging (networking); Transport engineering; Scheduling (production processes); Computer science; Automotive engineering; Engineering; Operations management; Computer security","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0005315699,0.001256341,0.001716512,0.0008642055,0.0006152865,0.001089014,0.0013705,0.001172968,0.005921962],"category_scores_gemma":[0.001133243,0.0003937225,0.0006497759,0.0007004113,0.0003000157,0.0009261734,0.0009384719,0.0007171907,0.000340216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007433904,"about_ca_system_score_gemma":0.001682293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006533175,"about_ca_topic_score_gemma":0.005002263,"domain_scores_codex":[0.9997041,0.00006540431,0.000009216798,0.00006400069,0.00002839304,0.0001289326],"domain_scores_gemma":[0.9993964,0.0001844429,0.00007522645,0.00002898808,0.0001128518,0.0002020691],"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":[0.000662823,0.0003506588,0.001811718,0.0001340983,0.00009049297,0.0001894989,0.0001219665,0.9467228,0.004622187,0.006820562,0.002270689,0.03620251],"study_design_scores_gemma":[0.00001065698,0.0001037249,0.0003023013,0.000004590167,0.00001830675,0.000008338387,0.00005206386,0.9980559,0.0002496266,0.001012338,0.0001776128,0.000004481366],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.488422,0.0004882384,0.492969,0.0006198498,0.0002406639,0.0002766624,0.0003262961,0.0005231649,0.01613409],"genre_scores_gemma":[0.986846,0.00007245743,0.01066446,0.00003816062,0.00003285643,0.00005971485,0.00009644489,0.00002250045,0.002167548],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006533175,"threshold_uncertainty_score":0.01981091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03676990018308829,"score_gpt":0.3318313501089281,"score_spread":0.2950614499258398,"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."}}