{"id":"W4317885027","doi":"10.32604/csse.2023.034230","title":"3D Object Detection with Attention: Shell-Based Modeling","year":2023,"lang":"en","type":"article","venue":"Computer Systems Science and Engineering","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Priority Academic Program Development of Jiangsu Higher Education Institutions; Nanjing University; Government of Jiangsu Province; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Point cloud; Computer science; Artificial intelligence; Minimum bounding box; Object detection; Computer vision; Weighting; Feature (linguistics); Object (grammar); Bounding overwatch; Feature extraction; Point (geometry); Lidar; Pattern recognition (psychology); Image (mathematics); Remote sensing; Mathematics","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":[0.0003638961,0.000120894,0.0001104131,0.0002830593,0.0003068522,0.0003293978,0.0004632113,0.00002447586,8.549209e-8],"category_scores_gemma":[0.000006791102,0.0001056647,0.00001549021,0.002289899,0.0000447963,0.0007026201,0.0001564196,0.00008801807,0.00001586881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005715116,"about_ca_system_score_gemma":0.00004583078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007855034,"about_ca_topic_score_gemma":0.000001141382,"domain_scores_codex":[0.9987033,0.000008402742,0.0001484636,0.0004546661,0.0003541609,0.0003310025],"domain_scores_gemma":[0.99932,0.00004321295,0.00003440889,0.0003676844,0.0001262835,0.0001084419],"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":[4.461715e-7,0.000002269806,0.00002946892,0.00002197054,0.000001700514,0.00000414307,0.00003713712,0.9874179,0.005139665,0.0007886351,0.00001041097,0.006546193],"study_design_scores_gemma":[0.00009918674,0.00003869772,0.0004504866,0.0000644032,0.000001719894,0.00003857736,0.000005785919,0.9986072,0.0002375795,0.000009864462,0.0003040973,0.0001423794],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06615958,0.00005109956,0.9321024,0.00006258578,0.0007232981,0.0001681252,2.247354e-7,0.0007059222,0.00002673944],"genre_scores_gemma":[0.9589859,0.000004962913,0.04071518,0.00002684774,0.000193232,0.00005152731,5.936329e-7,0.000009254675,0.00001247841],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8928263,"threshold_uncertainty_score":0.4308881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01514413620866092,"score_gpt":0.2121422539018736,"score_spread":0.1969981176932127,"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."}}