{"id":"W7128639328","doi":"10.1145/3768617.3770734","title":"Lightweight 1D UNet-CPCA Regression Model for Energy-Efficient Blood Pressure Estimation from Raw PPG Signals","year":2025,"lang":"","type":"article","venue":"","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Regression analysis; Linear regression; Regression; Pattern recognition (psychology); Photoplethysmogram; Estimation","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":[0.0005353443,0.0007324245,0.001003022,0.0003025107,0.000282994,0.0007602126,0.001124663,0.0008451883,0.003425233],"category_scores_gemma":[0.001579162,0.0003460135,0.0007957332,0.0004810164,0.0002277537,0.0008119812,0.0008318408,0.001467111,0.001636954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002471436,"about_ca_system_score_gemma":0.0008083994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006242871,"about_ca_topic_score_gemma":0.007000934,"domain_scores_codex":[0.9997157,0.00006228949,0.00001605364,0.00009132094,0.00008042215,0.00003414439],"domain_scores_gemma":[0.9997031,0.0001126695,0.00002295642,0.00003969526,0.0001069166,0.0000145591],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005914902,0.0002366809,0.001879194,0.0002796869,0.0002604476,0.0002584565,0.00007438906,0.4412716,0.03212011,0.008026588,0.007645179,0.5073562],"study_design_scores_gemma":[0.000006080837,0.00002912568,0.0003874161,0.000008311646,0.00001527336,0.00003503895,0.000002537037,0.9965425,0.001303103,0.0007232983,0.000938179,0.00000901806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008972384,0.0006125688,0.987833,0.0001624429,0.0001173958,0.000032017,0.0002371514,0.000901441,0.001131614],"genre_scores_gemma":[0.6234844,0.002424847,0.3550017,0.000398443,0.0003765959,0.0004450883,0.001868355,0.0003468606,0.0156536],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006242871,"threshold_uncertainty_score":0.01241308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01168636146872714,"score_gpt":0.2411561819873274,"score_spread":0.2294698205186003,"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."}}