{"id":"W4405855203","doi":"10.1016/j.aap.2024.107903","title":"Quantifying learning algorithm uncertainties in autonomous driving systems: Enhancing safety through Polynomial Chaos Expansion and High Definition maps","year":2024,"lang":"en","type":"article","venue":"Accident Analysis & Prevention","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Polynomial chaos; CHAOS (operating system); Algorithm; Computer science; Poison control; Polynomial; Engineering; Mathematics; Computer security; Medical emergency; Medicine; Monte Carlo method; Statistics","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":[0.001497231,0.0005512662,0.0004915667,0.0005887075,0.0003626265,0.001023112,0.0005758497,0.0006721606,0.0006595652],"category_scores_gemma":[0.007316188,0.0002379849,0.0003834023,0.0003552374,0.001156307,0.002169647,0.001588892,0.001015645,0.00008326276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007679954,"about_ca_system_score_gemma":0.0008112504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002190788,"about_ca_topic_score_gemma":0.001496807,"domain_scores_codex":[0.9994223,0.0001945651,0.00002367742,0.00009635853,0.000195366,0.00006769875],"domain_scores_gemma":[0.9964566,0.002526057,0.0003396277,0.0002088615,0.0003893702,0.00007949946],"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":[0.00007136077,0.00002489155,0.0007659387,0.00004463194,0.0000179553,0.00002627558,0.00007845605,0.9569959,0.003079394,0.01833704,0.0001011751,0.02045693],"study_design_scores_gemma":[0.000001311841,0.00002238459,0.0001883922,0.000002466068,0.000002795711,0.000006328656,0.000006522503,0.9935532,0.0008540329,0.005296574,0.0000617793,0.000004166583],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08947131,0.0001240366,0.9086913,0.0001901579,0.0000195971,0.00002130018,0.00002232683,0.00009067952,0.001369243],"genre_scores_gemma":[0.9710127,0.00009422853,0.02819174,0.00002333116,0.00001512274,0.00001589894,0.0000178037,0.00002425992,0.0006048622],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002190788,"threshold_uncertainty_score":0.007918179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06288564394510299,"score_gpt":0.3307815720782766,"score_spread":0.2678959281331736,"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."}}