{"id":"W4403372065","doi":"10.4017/gt.2024.23.s.886.opp","title":"Remote heart rate monitoring with contactless ambient technology using machine learning for aging population","year":2024,"lang":"en","type":"article","venue":"Gerontechnology","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Mitacs; Ontario Centre of Innovation","keywords":"Population; Computer science; Biomedical engineering; Medicine","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002112092,0.0003071607,0.0003584591,0.0007675948,0.000181688,0.00007973477,0.0001945689,0.0003309812,0.000003875697],"category_scores_gemma":[0.00006170262,0.0003084316,0.0000682377,0.0006673065,0.00007307118,0.0002257644,0.00008475898,0.0006746425,0.00001345368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004322341,"about_ca_system_score_gemma":0.00001968301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001458243,"about_ca_topic_score_gemma":0.00005378118,"domain_scores_codex":[0.9984901,0.00002321325,0.0003052502,0.0004434126,0.0001180459,0.0006199722],"domain_scores_gemma":[0.9994516,0.0001020801,0.0000442921,0.0002887492,0.00006080982,0.00005242001],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001918923,0.000006374031,0.02674074,0.0002468702,0.0001078378,0.00005729082,0.00006320066,0.01460355,0.9341305,0.0006007183,0.000006101473,0.0234176],"study_design_scores_gemma":[0.0006172757,0.0002611256,0.0007744091,0.0009580248,0.00008332783,0.0002727065,0.0002908648,0.1160161,0.8751163,0.002068675,0.002905089,0.0006360486],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7849558,0.003855934,0.2060566,0.0002206204,0.001244548,0.0003897628,0.000004801328,0.003239436,0.00003247784],"genre_scores_gemma":[0.9777757,0.00005651965,0.0216785,0.000004920586,0.0002441227,0.00004421033,0.00001083537,0.0001405919,0.0000445865],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1928199,"threshold_uncertainty_score":0.9999368,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01876576060990003,"score_gpt":0.2615838780992442,"score_spread":0.2428181174893442,"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."}}