{"id":"W3033771596","doi":"10.1155/2020/4040252","title":"Study on Accessibility of Feeder Lines with Different Geometric Shapes","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Line (geometry); Universality (dynamical systems); Transport engineering; Computer science; Routing (electronic design automation); Simulation; Engineering; Mathematics; Geometry; Computer network","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":[0.0005371819,0.0004165024,0.0003034116,0.001161903,0.0003117072,0.0007160884,0.0004658518,0.0004088265,0.001791924],"category_scores_gemma":[0.004360291,0.0001753211,0.0005412068,0.001092826,0.0004524797,0.001048564,0.0004765402,0.0003079955,0.0001941502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004440435,"about_ca_system_score_gemma":0.0002406282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001975578,"about_ca_topic_score_gemma":0.00150546,"domain_scores_codex":[0.9993681,0.0002089841,0.00002776044,0.0001226036,0.0001625365,0.0001100082],"domain_scores_gemma":[0.9964806,0.002061311,0.0005028074,0.0003103126,0.0005153256,0.0001296269],"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":[0.0004568441,0.0001951847,0.05489993,0.0001980611,0.0001089961,0.001038971,0.00046449,0.856104,0.02604756,0.01082692,0.000531176,0.04912802],"study_design_scores_gemma":[0.00003144848,0.0007218211,0.04809735,0.00002251237,0.0001152903,0.0007988932,0.0008134769,0.924601,0.01463746,0.008252069,0.00185711,0.00005156485],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9492802,0.0001520885,0.04586439,0.00004729354,0.00001110754,0.00003204723,0.0001655174,0.00007273955,0.004374664],"genre_scores_gemma":[0.9968908,0.00005738069,0.002616842,0.000002925236,0.000004305929,0.000007093362,0.0000788276,0.000008856738,0.0003330288],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001975578,"threshold_uncertainty_score":0.005994558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03873501919775113,"score_gpt":0.3296175391940304,"score_spread":0.2908825199962793,"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."}}