{"id":"W2109149546","doi":"10.1109/iembs.2006.260164","title":"Reliable Respiratory Rate Estimation from a Bed Pressure Array","year":2006,"lang":"en","type":"article","venue":"","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Élisabeth Bruyère Hospital; University of Ottawa; Carleton University","funders":"","keywords":"Weighting; Metric (unit); Reliability (semiconductor); Respiratory rate; Statistics; Computer science; Estimation; Variance (accounting); Mathematics; Engineering; Medicine","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":[0.00005773585,0.00009284317,0.000091697,0.00005960759,0.00004271887,0.00003470139,0.00009120174,0.0001120134,0.0002152832],"category_scores_gemma":[0.00002249041,0.00007508587,0.00002261381,0.000136175,0.00001926486,0.0001312821,0.000008927634,0.00007789624,0.000126837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001850809,"about_ca_system_score_gemma":0.000006623812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001512603,"about_ca_topic_score_gemma":0.00003523946,"domain_scores_codex":[0.9995212,0.000007816117,0.0001551358,0.0001083227,0.00007307606,0.0001344717],"domain_scores_gemma":[0.9997246,0.00002182717,0.00001681652,0.0001959083,0.00002687809,0.00001394809],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000005634848,0.00001468437,0.001595646,0.00003493204,0.00002682276,0.000002765346,0.00004708569,0.8665268,0.05652812,0.004654952,0.06829847,0.002264037],"study_design_scores_gemma":[0.0002875838,0.00001143752,0.001730914,0.00001535187,0.00001879619,2.289965e-7,0.00003063201,0.2135196,0.672682,0.006669184,0.104838,0.0001962227],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1266496,0.001337095,0.7790012,0.0001869317,0.0006427367,0.0003565617,0.00003737548,0.007677246,0.08411132],"genre_scores_gemma":[0.9912963,0.000006966253,0.007187176,0.00008208319,0.00006536522,0.00001883792,0.00003598387,0.0000231388,0.00128415],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8646467,"threshold_uncertainty_score":0.3061913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006198540463381286,"score_gpt":0.1923619126831859,"score_spread":0.1861633722198047,"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."}}