{"id":"W4385236452","doi":"10.1109/itec55900.2023.10186985","title":"Uncertainty Characterization for 3D Object Detection Algorithms","year":2023,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Artificial intelligence; Intersection (aeronautics); Computer science; Object detection; Computer vision; Object (grammar); Context (archaeology); Ground truth; Algorithm; Euclidean distance; Lidar; Measurement uncertainty; Measure (data warehouse); Sensor fusion; Pattern recognition (psychology); Mathematics; Data mining; 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":[],"consensus_categories":[],"category_scores_codex":[0.00007127723,0.00007101867,0.00006780546,0.00009067765,0.00005575961,0.00002809795,0.00002909427,0.00005536489,0.00002064286],"category_scores_gemma":[0.00001777117,0.00006978399,0.00002951406,0.0002790355,0.000004820884,0.00006509013,0.000004104906,0.00002923881,0.00005336448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000377068,"about_ca_system_score_gemma":0.000004560521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008400227,"about_ca_topic_score_gemma":0.00001539023,"domain_scores_codex":[0.9995819,0.000006141527,0.0001138601,0.00009327652,0.00006659888,0.0001382639],"domain_scores_gemma":[0.9998153,0.00002610616,0.00001145294,0.00007851836,0.00004163483,0.00002703086],"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":[0.000004352498,0.000003941062,0.00002268891,0.00004004266,0.00001223379,4.798745e-7,0.00005479867,0.8265318,0.08600369,0.0001696689,0.0001815955,0.08697465],"study_design_scores_gemma":[0.0001510282,0.00002289457,0.0008263516,0.000004337367,0.000005708779,5.124571e-7,0.00001676865,0.9749813,0.0187504,0.00006680034,0.005081975,0.00009192199],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03982122,0.000002502878,0.9581689,0.00003363609,0.0005489678,0.00019966,0.0000133428,0.0008457408,0.0003660526],"genre_scores_gemma":[0.9948831,0.00005443692,0.003138629,0.00005583929,0.0002395113,0.00005876623,0.0007056525,0.0000464696,0.0008176008],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9550619,"threshold_uncertainty_score":0.2845709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01423241799047248,"score_gpt":0.2223417625816851,"score_spread":0.2081093445912126,"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."}}