{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006619532,0.0005426559,0.0005428981,0.0005374787,0.0001760344,0.000480774,0.000497528,0.0006337186,0.001083131],"category_scores_gemma":[0.001022963,0.0001986538,0.0003802253,0.0003898069,0.0001469474,0.0008725234,0.0008623707,0.0006584037,0.0006511208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002132012,"about_ca_system_score_gemma":0.0002957608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00049041,"about_ca_topic_score_gemma":0.0005575774,"domain_scores_codex":[0.9994842,0.00009843413,0.00002065177,0.000115454,0.0002167777,0.00006454607],"domain_scores_gemma":[0.9996436,0.00008675532,0.00005215488,0.00004727857,0.0001513975,0.00001881691],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009685482,0.0002703163,0.003540032,0.0002989721,0.0001141863,0.0003511361,0.0002988093,0.03949331,0.3033932,0.004621628,0.005695644,0.6409542],"study_design_scores_gemma":[0.00005313011,0.0007016971,0.005861043,0.00004733288,0.0001108572,0.0008046938,0.0001218739,0.8518904,0.122051,0.003566941,0.01472222,0.00006879732],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1400541,0.002256765,0.8481915,0.0004699534,0.0003790669,0.00007907943,0.0002665001,0.001505154,0.006797893],"genre_scores_gemma":[0.8764236,0.0007187593,0.1185331,0.000359604,0.0001660674,0.00005914126,0.0003795549,0.0000446214,0.003315529],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001083131,"threshold_uncertainty_score":0.003623426,"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."}}