{"id":"W2101013891","doi":"10.1109/iembs.2005.1616531","title":"Adaptive Change Point Detection for Respiratory Variables","year":2005,"lang":"en","type":"article","venue":"","topic":"Hemodynamic Monitoring and Therapy","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital; University of British Columbia","funders":"","keywords":"CUSUM; Computer science; Change detection; Kalman filter; Noise (video); Adaptive filter; Constant false alarm rate; Maximization; Algorithm; Artificial intelligence; Statistics; Mathematics; Mathematical optimization","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":[0.0001730329,0.00006408907,0.0001010814,0.00005142198,0.00004584562,0.000004531375,0.00002080017,0.00005904634,0.00006766666],"category_scores_gemma":[0.00002091162,0.00005124109,0.00004349698,0.00004970004,0.0000108504,0.00005819404,0.000004766434,0.00005746071,0.00002532183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000831105,"about_ca_system_score_gemma":0.0000204514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004886935,"about_ca_topic_score_gemma":0.00002544088,"domain_scores_codex":[0.9995691,0.00001083541,0.00009381532,0.0001228761,0.00007249233,0.0001308799],"domain_scores_gemma":[0.9997064,0.00003617683,0.00002090626,0.0001209958,0.00005393864,0.00006156218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004346604,0.0001185101,0.0003401005,0.00002892462,0.00006294499,0.000002082404,0.0003793747,0.000004789596,0.02616939,0.001990943,0.0005433828,0.9699249],"study_design_scores_gemma":[0.006115041,0.00290563,0.01130658,0.0001572111,0.0001061517,0.0000345138,0.0004914319,0.03019668,0.2427578,0.001231301,0.7043077,0.0003898769],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6170347,0.0009541154,0.3353012,0.003973778,0.001301663,0.002516616,0.00001459667,0.0007407492,0.03816267],"genre_scores_gemma":[0.9881103,0.00001244735,0.006766439,0.001224823,0.001847627,0.0001349087,0.000001643132,0.00001533574,0.001886466],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.969535,"threshold_uncertainty_score":0.2089551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06852656218711076,"score_gpt":0.3127075841360499,"score_spread":0.2441810219489391,"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."}}