{"id":"W4413822039","doi":"10.1109/ojits.2025.3603968","title":"Roadside Fisheye Vision for Cooperative Perception in V2I-Assisted Automated Driving","year":2025,"lang":"en","type":"article","venue":"IEEE Open Journal of Intelligent Transportation Systems","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; McMaster University Medical Centre","funders":"","keywords":"Perception; Computer science; Computer vision; Artificial intelligence; Human–computer interaction; Psychology","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":[0.0007420586,0.0001680942,0.0003989697,0.0003355803,0.0001447123,0.0003357275,0.001028023,0.00008247379,0.000004776663],"category_scores_gemma":[0.00003495864,0.0001494865,0.0001103382,0.0009125858,0.00002672383,0.001340767,0.00001345864,0.000185162,0.000005909744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000209415,"about_ca_system_score_gemma":0.0001673283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005253775,"about_ca_topic_score_gemma":0.0003276092,"domain_scores_codex":[0.9977682,0.0001400516,0.001325504,0.0003053387,0.0002577348,0.0002032358],"domain_scores_gemma":[0.9980948,0.0002764583,0.0005871844,0.0002644287,0.0006967858,0.00008032281],"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":[0.0002821607,0.0005446961,0.006594442,0.0001517153,0.000169084,0.00005001266,0.004774321,0.8399338,0.07307939,0.01756295,0.009085532,0.04777186],"study_design_scores_gemma":[0.002472555,0.0005867634,0.1060043,0.002729312,0.00006630838,0.00005731479,0.002054007,0.8639039,0.0117298,0.001015569,0.008835765,0.0005444058],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1022622,0.0001010822,0.8946384,0.0005764289,0.0009857342,0.001212429,0.000005279654,0.00006353734,0.0001548405],"genre_scores_gemma":[0.980868,0.00006804692,0.01844034,0.000110667,0.00004952943,0.0001221305,0.00001566134,0.00001210138,0.0003135562],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8786057,"threshold_uncertainty_score":0.6095884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0321283311807188,"score_gpt":0.3559648876215952,"score_spread":0.3238365564408764,"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."}}