{"id":"W3194216936","doi":"10.1109/antem51107.2021.9518503","title":"Passenger Monitoring Using AI-Powered Radar","year":2021,"lang":"en","type":"article","venue":"","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Radar; Occupancy; Computer science; Real-time computing; Man-portable radar; Fire-control radar; Radar engineering details; Radar tracker; Radar lock-on; Artificial intelligence; Radar imaging; Computer vision; Engineering; 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":[0.00006444733,0.0001931587,0.0001864177,0.00006996032,0.00007330682,0.00009397107,0.000110955,0.00009200782,0.0001625721],"category_scores_gemma":[0.00003716103,0.0002134208,0.00008057091,0.000320305,0.0000142292,0.0002853873,0.00006971526,0.0002182975,0.00008860166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001751425,"about_ca_system_score_gemma":0.0000336665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002114144,"about_ca_topic_score_gemma":0.000003562057,"domain_scores_codex":[0.998952,0.00002028343,0.0002088343,0.0002210005,0.0002148143,0.0003830149],"domain_scores_gemma":[0.9994199,0.00005674279,0.0000144446,0.000303001,0.00008320703,0.0001226629],"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":[0.000001146977,0.00001042597,0.01209189,0.00003923568,0.00004813544,0.000143244,0.00005808446,0.001375844,0.9841644,0.0001460402,0.0001681821,0.001753324],"study_design_scores_gemma":[0.0002091418,0.000006039857,0.001115003,0.00007277561,0.00001655565,0.00003405337,0.0001722283,0.0008156673,0.9950176,0.0002154513,0.002013337,0.00031207],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8983265,0.002539594,0.06504652,0.0000830734,0.006554666,0.0001508553,0.000005628235,0.00130525,0.0259879],"genre_scores_gemma":[0.9793363,0.0000629916,0.01934928,0.00002080533,0.0009264323,0.000005110047,0.000002060011,0.00007420155,0.0002228809],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08100972,"threshold_uncertainty_score":0.8703048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02145242754857137,"score_gpt":0.2503291788833612,"score_spread":0.2288767513347899,"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."}}