{"id":"W3011164092","doi":"10.23919/fusion43075.2019.9011188","title":"Extracting human breathing rate from the fusion of multiple piezo-resistive membranes","year":2019,"lang":"en","type":"article","venue":"","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thales (Canada)","funders":"","keywords":"Sensor fusion; Computer science; Resistive touchscreen; Breathing; Real-time computing; Work (physics); Continuous monitoring; Simulation; Engineering; Artificial intelligence; Computer vision; Medicine; Mechanical engineering","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":[0.0003351862,0.0005578378,0.0005520297,0.0007889975,0.0001236073,0.0004299523,0.000272757,0.0007383836,0.0007813944],"category_scores_gemma":[0.0007326116,0.000137177,0.0005818767,0.0004412306,0.00013894,0.0004600546,0.0004353286,0.0003003608,0.000499566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009857915,"about_ca_system_score_gemma":0.0001184442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002693497,"about_ca_topic_score_gemma":0.0003237904,"domain_scores_codex":[0.999768,0.00002423486,0.00001754793,0.00006622584,0.00009519783,0.00002888178],"domain_scores_gemma":[0.9998612,0.00003950047,0.00002536778,0.00001662381,0.00004631287,0.00001083861],"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":[0.0006873904,0.0001608017,0.006643183,0.0003170471,0.0001170167,0.000463075,0.0001446867,0.01512487,0.5269557,0.0003796009,0.001025811,0.4479808],"study_design_scores_gemma":[0.00005447096,0.001248475,0.09061852,0.0001103337,0.0002390591,0.002995176,0.0003431722,0.5366838,0.3605338,0.001750086,0.005308266,0.0001148962],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4666031,0.001589998,0.5268426,0.0002273635,0.0002025826,0.0001088879,0.000647623,0.001361191,0.002416599],"genre_scores_gemma":[0.9234284,0.0006180928,0.07393983,0.00006459688,0.00004929254,0.00005104213,0.0003670776,0.00004166252,0.001439958],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0007889975,"threshold_uncertainty_score":0.002614021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0137807947498271,"score_gpt":0.2221311097389849,"score_spread":0.2083503149891578,"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."}}