{"id":"W3110786550","doi":"10.1109/smc42975.2020.9283398","title":"Video-Based Breathing Rate Monitoring in Sleeping Subjects","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 Calgary","funders":"","keywords":"Breathing; Computer science; Artificial intelligence; Computer vision; Region of interest; Respiratory rate; Wearable computer; Optical flow; Pattern recognition (psychology); Medicine; Heart rate; Image (mathematics)","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":[0.0002008392,0.0003433605,0.0003722416,0.0006353057,0.00006877736,0.0002447088,0.0003001229,0.0004069184,0.0006064487],"category_scores_gemma":[0.0009423753,0.00007427245,0.0001274355,0.000322039,0.00008345831,0.0002019728,0.0001606588,0.0001643086,0.0003320749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007826254,"about_ca_system_score_gemma":0.0001030118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001409909,"about_ca_topic_score_gemma":0.002851878,"domain_scores_codex":[0.9998195,0.00004335198,0.00001107204,0.00005994223,0.00005104688,0.00001513318],"domain_scores_gemma":[0.9996563,0.0001363897,0.00007037478,0.00002214147,0.0000846146,0.00003007661],"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":[0.002147148,0.0003902183,0.06903776,0.001449742,0.0001929213,0.000677307,0.0003337122,0.009404217,0.3872583,0.000324073,0.003274351,0.5255103],"study_design_scores_gemma":[0.0001616122,0.002444201,0.63212,0.0002041183,0.0002780419,0.004548831,0.0004421999,0.2297055,0.1220545,0.000786456,0.007157924,0.00009659271],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8890687,0.002889526,0.1010112,0.0001450322,0.0001356863,0.0001652074,0.002584597,0.0009295876,0.00307043],"genre_scores_gemma":[0.9583607,0.001024731,0.03709377,0.0001089928,0.0001357361,0.000075381,0.001904415,0.00004215522,0.00125414],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001409909,"threshold_uncertainty_score":0.002803385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02102472540915941,"score_gpt":0.2227850107310985,"score_spread":0.2017602853219391,"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."}}