{"id":"W4404215451","doi":"10.1038/s41598-024-77171-6","title":"Novel metrics for tracking blood pressure changes incontinuous cuffless blood pressure estimations","year":2024,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Blood pressure; Computer science; Medicine; 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":[0.003692885,0.001138452,0.0009175167,0.003747925,0.0003203423,0.001795713,0.0008725225,0.0009645494,0.0006940259],"category_scores_gemma":[0.01588981,0.000187075,0.0005908582,0.002200467,0.000462406,0.002058039,0.001090781,0.0006673037,0.0003261934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004292062,"about_ca_system_score_gemma":0.0005698273,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001317713,"about_ca_topic_score_gemma":0.001000128,"domain_scores_codex":[0.9959128,0.001055062,0.0005056034,0.000548431,0.00185269,0.0001253528],"domain_scores_gemma":[0.9936001,0.002427868,0.001027837,0.000504127,0.002229737,0.0002102446],"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":[0.0009827076,0.0003650895,0.04784977,0.0009372644,0.0004782121,0.0002029608,0.0004877858,0.08252186,0.05448608,0.0097993,0.00413716,0.7977518],"study_design_scores_gemma":[0.0000459499,0.001624709,0.0496555,0.000160228,0.0002358607,0.000818664,0.0002859917,0.9014969,0.03118674,0.006205316,0.008123428,0.0001606224],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1039566,0.002781423,0.8880574,0.0001522997,0.0002911894,0.0001723068,0.0005861547,0.001506977,0.002495604],"genre_scores_gemma":[0.6813646,0.001133894,0.3146386,0.0001012571,0.0002006212,0.0002761925,0.001013656,0.0001235354,0.001147608],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003747925,"threshold_uncertainty_score":0.01953006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02372333871716568,"score_gpt":0.2562865424666596,"score_spread":0.2325632037494939,"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."}}