{"id":"W4293564020","doi":"10.1016/j.physa.2022.128077","title":"Temporal robustness assessment framework for city-scale bus transit networks","year":2022,"lang":"en","type":"article","venue":"Physica A Statistical Mechanics and its Applications","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Robustness (evolution); Computer science; Bus rapid transit; Scale (ratio); Transport engineering; Public transport; Engineering; Geography; Cartography","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":[0.005240706,0.001197409,0.001224314,0.002018315,0.0005408507,0.001926785,0.002184917,0.001343842,0.003217345],"category_scores_gemma":[0.01276812,0.0004919823,0.001582286,0.00117525,0.001259419,0.002389577,0.002122421,0.001289139,0.0002770472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001591457,"about_ca_system_score_gemma":0.001478229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005362363,"about_ca_topic_score_gemma":0.002778899,"domain_scores_codex":[0.9983048,0.0006139415,0.00007709616,0.0004321856,0.0003912086,0.0001806893],"domain_scores_gemma":[0.9931189,0.004372812,0.0008616421,0.0003911032,0.0009938619,0.0002616789],"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":[0.00008177741,0.00002981304,0.0008937735,0.0001088107,0.0001463134,0.0001299022,0.00004647673,0.9017084,0.001580568,0.07906275,0.001100168,0.0151113],"study_design_scores_gemma":[0.000002630055,0.00001552687,0.0001630791,0.000005413182,0.00001695971,0.00001207938,0.000007469771,0.9851627,0.0001801199,0.01418987,0.0002390282,0.000005214511],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01244717,0.0002741147,0.9846507,0.0002366748,0.00003329745,0.00004352708,0.0001896558,0.000156301,0.001968494],"genre_scores_gemma":[0.911716,0.000864386,0.07948959,0.0001680281,0.0002613225,0.0002603327,0.0006877288,0.0001514376,0.006401092],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005362363,"threshold_uncertainty_score":0.02771586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02401212846337861,"score_gpt":0.326660912718899,"score_spread":0.3026487842555203,"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."}}