{"id":"W7140150998","doi":"","title":"Road network vulnerability analysis with consideration of probability and consequences of disruptive events","year":2020,"lang":"en","type":"dissertation","venue":"Open MIND","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Hong Kong Polytechnic University","keywords":"Vulnerability (computing); Vulnerability assessment; Closure (psychology); Extreme weather; Network analysis; Extreme value theory; Vulnerability index; Poison control","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004407307,0.0002566066,0.0009917404,0.0000986836,0.00007356074,0.00004465154,0.0002279472,0.0001884142,0.0005132274],"category_scores_gemma":[0.0001311042,0.000210804,0.0001419446,0.0008412702,0.0002269552,0.0002100017,0.00003067993,0.0002443587,0.00000146075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004368816,"about_ca_system_score_gemma":0.0001694176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002870651,"about_ca_topic_score_gemma":0.004486688,"domain_scores_codex":[0.9983122,0.0001608415,0.0006543325,0.0004433967,0.0002666626,0.0001625867],"domain_scores_gemma":[0.9989045,0.0001288163,0.0003233993,0.0003301256,0.0002406913,0.00007246125],"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":[0.0008368937,0.0001301253,0.1573022,0.001397337,0.006989101,0.000006533639,0.009079011,0.7631032,0.003798343,0.0001725672,0.00002493693,0.05715972],"study_design_scores_gemma":[0.001750207,0.001040123,0.6991803,0.001031161,0.01793215,0.000008692694,0.01027503,0.09652096,0.1562142,0.01356602,0.0002145858,0.002266562],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952484,0.0001754799,0.0009663264,0.00001965784,0.0000452324,0.0006566842,0.00009538753,0.000003144661,0.002789634],"genre_scores_gemma":[0.9914513,0.00003057657,0.00793699,0.000002136267,0.00001836679,0.0000258726,0.0004786523,0.00001119355,0.00004488227],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6665823,"threshold_uncertainty_score":0.8596337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01984850211865901,"score_gpt":0.2881314660442562,"score_spread":0.2682829639255972,"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."}}