{"id":"W3159614872","doi":"10.1002/eng2.12413","title":"Improving passenger safety in cars using novel radar signal processing","year":2021,"lang":"en","type":"article","venue":"Engineering Reports","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Centres of Excellence","keywords":"Radar; Computer science; Robustness (evolution); Real-time computing; Signal processing; Doppler radar; Radar systems; SIGNAL (programming language); Simulation; Acoustics; Telecommunications; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002866723,0.0004381527,0.0002227003,0.0004557313,0.0001081063,0.0003543156,0.0003772702,0.0004837218,0.001080611],"category_scores_gemma":[0.0005038987,0.0001188489,0.0002054738,0.0002041008,0.0001683711,0.0003401948,0.0002968238,0.0002350289,0.0004637201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001188853,"about_ca_system_score_gemma":0.0001462979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003374249,"about_ca_topic_score_gemma":0.0003213793,"domain_scores_codex":[0.9997773,0.00004637793,0.000009172322,0.00004819392,0.00009599818,0.00002300266],"domain_scores_gemma":[0.9996855,0.00008249847,0.00004785307,0.00002371826,0.0001454564,0.00001488998],"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":[0.000379012,0.0001700308,0.00440451,0.0002815646,0.00004795812,0.0002293437,0.0001183576,0.01337436,0.7021859,0.0008913917,0.00171477,0.2762029],"study_design_scores_gemma":[0.00006334011,0.001472348,0.01004649,0.00005269898,0.0001003308,0.0008654508,0.0001242096,0.4085819,0.5698271,0.0007109608,0.008095065,0.00006012847],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3556558,0.001470031,0.6360841,0.0003419968,0.0002828572,0.0001035028,0.0001277538,0.00164266,0.004291179],"genre_scores_gemma":[0.8897088,0.0004290437,0.1074732,0.0001849325,0.00009781608,0.00003093259,0.0001281166,0.00002979574,0.001917493],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001080611,"threshold_uncertainty_score":0.003614962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008904088579399424,"score_gpt":0.2017890538890531,"score_spread":0.1928849653096537,"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."}}