{"id":"W2893895554","doi":"10.1287/ijoc.2017.0795","title":"Risk Averse Shortest Paths: A Computational Study","year":2018,"lang":"en","type":"article","venue":"INFORMS journal on computing","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Shortest path problem; Measure (data warehouse); Mathematical optimization; Risk measure; Variance (accounting); Mathematics; Path (computing); Regular polygon; Implementation; Arc length; Computer science; Arc (geometry); Discrete mathematics; Data mining","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":[0.002695954,0.0006241183,0.001240615,0.001040924,0.00087143,0.001476638,0.002126547,0.001682169,0.006060121],"category_scores_gemma":[0.02349536,0.0004456498,0.0007901574,0.002258119,0.001257676,0.003344202,0.001360478,0.002353159,0.000275585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001504514,"about_ca_system_score_gemma":0.001402176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006387098,"about_ca_topic_score_gemma":0.007895035,"domain_scores_codex":[0.9989961,0.0005276817,0.0000389633,0.0001526568,0.0001953575,0.0000892842],"domain_scores_gemma":[0.9671682,0.0297072,0.0008659106,0.001254594,0.0006672494,0.0003370345],"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":[0.00008475286,0.0001033494,0.001437071,0.0001019994,0.00002979154,0.00008759745,0.0000720546,0.9305958,0.0001381022,0.05598872,0.001386161,0.009974583],"study_design_scores_gemma":[0.00001366149,0.00001711738,0.0001163887,0.000009270689,0.000005372201,0.00002403446,0.00003039399,0.9813887,0.00008075708,0.01781016,0.0005002175,0.000003903825],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.474323,0.001670474,0.4915741,0.004145873,0.0001666616,0.0001703272,0.0008488657,0.0002839706,0.02681672],"genre_scores_gemma":[0.7930165,0.0008032328,0.201496,0.0001624942,0.00009002881,0.0002042681,0.0006420753,0.0001052911,0.003480113],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006387098,"threshold_uncertainty_score":0.02027315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06202038414082085,"score_gpt":0.3816068146451262,"score_spread":0.3195864305043054,"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."}}