{"id":"W4244433422","doi":"10.1109/cavs.2019.8887839","title":"CAVS 2019 Panel","year":2019,"lang":"en","type":"article","venue":"","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"National Institute of Standards and Technology","keywords":"Standardization; Interoperability; Session (web analytics); Reliability (semiconductor); Computer science; Energy consumption; Safety standards; Test (biology); Efficient energy use; Risk analysis (engineering); Engineering management; Reliability engineering; Business; Engineering","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00003007947,0.00005153559,0.00006534422,0.00002481205,0.00001048727,0.000002722051,0.00008253749,0.00008788295,0.0009711181],"category_scores_gemma":[0.000001113311,0.00004642278,0.00001840369,0.0000437759,0.000009966597,0.00004045049,0.00001462684,0.00009813935,0.005458243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001425409,"about_ca_system_score_gemma":0.00000359326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007268132,"about_ca_topic_score_gemma":0.000003472307,"domain_scores_codex":[0.9997283,0.000001835163,0.00006105004,0.00006268446,0.00002645597,0.0001196632],"domain_scores_gemma":[0.9998005,0.000009785489,0.000003746642,0.0001657719,0.000004152917,0.00001601316],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002666679,0.00009764277,0.1962089,0.0001906053,0.0003390508,0.00003976416,0.0006202196,0.04498803,0.089569,0.3058226,0.1357045,0.226393],"study_design_scores_gemma":[0.001648273,0.0001542577,0.2462611,0.00002570737,0.00002614971,0.00006765395,0.0002520898,0.2666045,0.07323854,0.007627346,0.4027623,0.001332074],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7272527,0.0001352805,0.001888463,0.0001618949,0.0002608288,0.00007693737,0.000001461143,0.001581096,0.2686413],"genre_scores_gemma":[0.9902618,0.00001921479,0.0004752343,0.00005972651,0.00001128884,0.000001780566,0.000001894656,0.0000101804,0.009158882],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2981953,"threshold_uncertainty_score":0.9999421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00509107935922335,"score_gpt":0.1635986914692898,"score_spread":0.1585076121100664,"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."}}