{"id":"W4408703633","doi":"10.1109/emts57498.2023.10925281","title":"Radar Fusion for Enhanced Driver Monitoring","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Optical Sensing Technologies","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Fusion; Computer science; Radar; Sensor fusion; Remote sensing; Computer vision; Geology; Telecommunications","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":[0.00002385783,0.00005951915,0.00006995488,0.00002704834,0.00007844608,0.00001123229,0.00006814155,0.00002159148,0.00003294603],"category_scores_gemma":[0.00001336233,0.00005002694,0.00003868498,0.0001321684,0.00002251097,0.00005065444,0.0000680767,0.00004566095,0.000102212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008779448,"about_ca_system_score_gemma":0.000003803431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000609041,"about_ca_topic_score_gemma":1.474478e-7,"domain_scores_codex":[0.9995793,0.000001988284,0.00006618493,0.0001254786,0.0000493993,0.0001777226],"domain_scores_gemma":[0.9997402,0.00007740819,0.0000166277,0.0001223993,0.00002439954,0.00001892394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001277481,0.00002481194,0.002883347,0.000005324604,0.00002370431,6.661953e-7,0.00006122872,0.0002054135,0.4796819,0.118189,0.001412458,0.3974994],"study_design_scores_gemma":[0.0002373935,0.00002415888,0.00120703,0.00001135824,0.000004529479,2.425304e-8,0.0003738881,0.0005560947,0.8952292,0.09779938,0.004444505,0.0001124685],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6499354,0.00000260239,0.343161,0.0002642918,0.0002157615,0.0001477745,0.000003343248,0.0006745269,0.005595279],"genre_scores_gemma":[0.9304218,0.000001420493,0.06763949,0.000003808758,0.0001351979,0.00001400986,0.000005779975,0.000009500385,0.001769012],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4155473,"threshold_uncertainty_score":0.2040039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01919654896117905,"score_gpt":0.2893608200741465,"score_spread":0.2701642711129674,"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."}}