{"id":"W4312355099","doi":"10.1109/access.2022.3229977","title":"ReViSe: Remote Vital Signs Measurement Using Smartphone Camera","year":2022,"lang":"en","type":"article","venue":"IEEE Access","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Mitacs","keywords":"Computer science; Vital signs; Computer vision; Computer graphics (images)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002490465,0.0009842527,0.0005392236,0.0003332146,0.0001732801,0.0005788631,0.0007364773,0.0006302164,0.005415436],"category_scores_gemma":[0.001290204,0.0001726733,0.0002764991,0.000186292,0.0001097668,0.0005662269,0.0006962287,0.0005681016,0.003876114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003037088,"about_ca_system_score_gemma":0.0003208683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005025788,"about_ca_topic_score_gemma":0.008597732,"domain_scores_codex":[0.999669,0.00003734499,0.00002524167,0.0001134202,0.0001144956,0.00004045399],"domain_scores_gemma":[0.9996821,0.0000436977,0.00002142534,0.00008771139,0.0001366601,0.00002838183],"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":[0.001171689,0.000394341,0.02570044,0.001028761,0.0002393481,0.001242491,0.0002001392,0.01220224,0.1340313,0.001631696,0.1207762,0.7013814],"study_design_scores_gemma":[0.0002963207,0.001334982,0.1675946,0.0002337174,0.000163078,0.003452521,0.0002861945,0.5211352,0.198826,0.002988104,0.1034547,0.000234664],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3067625,0.004843829,0.4532647,0.002218043,0.002274357,0.001854945,0.06276676,0.1434492,0.02256562],"genre_scores_gemma":[0.821641,0.001166245,0.1182918,0.001099699,0.0002881868,0.0005150313,0.03966451,0.0005878544,0.01674571],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005415436,"threshold_uncertainty_score":0.01811647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07611889205603997,"score_gpt":0.2822432501566999,"score_spread":0.20612435810066,"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."}}