{"id":"W3082231457","doi":"10.1109/embc44109.2020.9175754","title":"A Joint Localization Assisted Respiratory Rate Estimation using IR-UWB Radars","year":2020,"lang":"en","type":"article","venue":"","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Breathing; Radar; Respiratory rate; Radar tracker; Computer vision; Track (disk drive); Impulse (physics); Artificial intelligence; Respiratory monitoring; Joint (building); Remote sensing; Simulation; Real-time computing; Telecommunications; Engineering; Respiratory system; Geology; Medicine; Physics; Heart rate","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":[0.0003549946,0.0005162979,0.0008149837,0.0004933862,0.0001537982,0.0004737146,0.0004382473,0.0006354259,0.001446501],"category_scores_gemma":[0.0006437346,0.0001922029,0.0003922131,0.0004158823,0.00009951466,0.0004741315,0.0004203239,0.0003736492,0.001047546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008350536,"about_ca_system_score_gemma":0.0002178512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000545949,"about_ca_topic_score_gemma":0.000531226,"domain_scores_codex":[0.9996119,0.00008669038,0.00002044332,0.0001307195,0.0001225884,0.00002758731],"domain_scores_gemma":[0.9997922,0.00004786982,0.00003170526,0.00002632427,0.00008143202,0.00002058302],"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":[0.000973451,0.0002684272,0.007867058,0.0005301993,0.0001794217,0.0004744246,0.0001851585,0.01835877,0.3778391,0.0009935972,0.00315679,0.5891736],"study_design_scores_gemma":[0.0002298829,0.001761296,0.03833525,0.0001262078,0.000295171,0.002933722,0.0001346056,0.726201,0.2164259,0.001017869,0.01234601,0.000193097],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08786433,0.001736101,0.9045134,0.0001779398,0.0002833922,0.00006980423,0.0002657985,0.002637748,0.002451544],"genre_scores_gemma":[0.7234377,0.001323785,0.2683648,0.0002057992,0.0001365944,0.0001198322,0.0004335739,0.00007267776,0.005905206],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001446501,"threshold_uncertainty_score":0.004839063,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06392173848627519,"score_gpt":0.2501780705065868,"score_spread":0.1862563320203116,"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."}}