{"id":"W4238969329","doi":"10.22215/etd/2016-11575","title":"A Simulation-Based Approach to the Characterisation of Urban Traffic Network Vulnerability","year":2016,"lang":"en","type":"dissertation","venue":"","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Vulnerability (computing); Centrality; Vulnerability index; Computer science; Vulnerability assessment; Mesoscopic physics; Transport engineering; Data mining; Engineering; Mathematics; Computer security; Statistics; Geology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004443339,0.0002772263,0.000411957,0.000124479,0.0001311005,0.00003321714,0.0002896073,0.000265051,0.0002280288],"category_scores_gemma":[0.0001717143,0.0001706702,0.0002289292,0.0004844099,0.00002867512,0.00008333834,0.000005584461,0.0002418166,0.00001931312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009415503,"about_ca_system_score_gemma":0.00006405742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001415928,"about_ca_topic_score_gemma":0.0001004609,"domain_scores_codex":[0.9984722,0.00009600452,0.0005388784,0.0003047263,0.000325166,0.0002630496],"domain_scores_gemma":[0.9986131,0.0004608387,0.0001157394,0.0005727293,0.0001735395,0.00006407305],"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":[0.00003269195,0.00002023316,0.0002236092,0.0002010878,0.00005757194,3.65641e-8,0.0004688516,0.986865,0.0001608839,0.00006027561,0.000278625,0.01163113],"study_design_scores_gemma":[0.0001147688,0.00002300505,0.01040633,0.00006122088,0.0001016237,4.598812e-8,0.0001428725,0.9869609,0.0007101495,0.0000675795,0.001133771,0.0002776781],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.691901,0.0001442709,0.2928255,0.00007776668,0.0008852773,0.00129873,0.000061533,0.0003190449,0.01248696],"genre_scores_gemma":[0.9978628,0.00000306549,0.0005900489,0.00003982133,0.0004030029,0.0000883535,0.0005474774,0.00003441819,0.0004310326],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3059618,"threshold_uncertainty_score":0.695973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008749859809470855,"score_gpt":0.2388636349171088,"score_spread":0.2301137751076379,"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."}}