{"id":"W2518269327","doi":"10.1109/memea.2016.7533751","title":"An integrated system to compensate for temperature drift and ageing in non-invasive blood pressure measurement","year":2016,"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 Ottawa","funders":"","keywords":"Hilbert–Huang transform; Blood pressure; Noise (video); SIGNAL (programming language); Temperature measurement; Pressure sensor; Ageing; Computer science; Environmental science; Materials science; Acoustics; Electronic engineering; Artificial intelligence; Engineering; Medicine; Telecommunications; Physics; Internal 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001059812,0.0007123941,0.0009624422,0.0008006659,0.0003927018,0.0008868449,0.002038514,0.001167315,0.003791971],"category_scores_gemma":[0.001688435,0.0003753704,0.0004214186,0.0005173469,0.0002211406,0.001005999,0.0009074022,0.0005832363,0.002215013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003009174,"about_ca_system_score_gemma":0.0005991497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006286393,"about_ca_topic_score_gemma":0.0008017687,"domain_scores_codex":[0.9990595,0.0001022761,0.00007470829,0.000298111,0.000403022,0.00006241433],"domain_scores_gemma":[0.9991598,0.0001249731,0.00009101981,0.0001532576,0.0004179651,0.00005295799],"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":[0.001141911,0.0007252496,0.005509238,0.0005183664,0.0002056369,0.0005013427,0.000363375,0.005094984,0.4432208,0.001987619,0.01006322,0.5306683],"study_design_scores_gemma":[0.0004731207,0.004521402,0.02651424,0.0001763519,0.0006774197,0.00401991,0.00009377724,0.4809851,0.4106917,0.001847294,0.06966372,0.0003359164],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05352402,0.0008146841,0.9280971,0.0002295363,0.0007387873,0.0003910028,0.0002558155,0.01319841,0.002750662],"genre_scores_gemma":[0.4474297,0.0004217464,0.5380623,0.0007990141,0.0004132185,0.0006357656,0.0006693951,0.0003419021,0.01122711],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003791971,"threshold_uncertainty_score":0.01268536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01079022488060856,"score_gpt":0.2105950550963983,"score_spread":0.1998048302157897,"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."}}