{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00304592,0.001049785,0.0009612215,0.003216177,0.0007225843,0.002233447,0.001276957,0.00131582,0.0009315091],"category_scores_gemma":[0.02377446,0.0006897361,0.001048783,0.001894977,0.001319302,0.003085258,0.002488205,0.001103066,0.0002760552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001391159,"about_ca_system_score_gemma":0.0008643792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00317322,"about_ca_topic_score_gemma":0.002125187,"domain_scores_codex":[0.9968225,0.0004893218,0.0002603412,0.0004769223,0.001765766,0.0001850603],"domain_scores_gemma":[0.9919242,0.005239752,0.0007585371,0.0007064709,0.001222222,0.0001487975],"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":[0.0002678795,0.00005149651,0.007100893,0.0002205192,0.0001171774,0.0001324933,0.0002649451,0.7623616,0.01475987,0.02317784,0.0008239278,0.1907213],"study_design_scores_gemma":[0.000003422635,0.00004067393,0.001446106,0.0000210116,0.000009617846,0.00009494276,0.00003165931,0.9796873,0.00743988,0.01048516,0.0007148376,0.00002533148],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0261679,0.0005151778,0.9718961,0.00009806439,0.00001926489,0.0000307975,0.0001172325,0.0003909247,0.0007645946],"genre_scores_gemma":[0.7856383,0.0005678647,0.2119672,0.0001236578,0.00007391861,0.000157422,0.0006107208,0.0002317801,0.0006291621],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003216177,"threshold_uncertainty_score":0.01610851,"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."}}