{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003723075,0.0002268699,0.0002338216,0.0001499856,0.0002764369,0.0001390503,0.0005464726,0.00003966973,0.0001840347],"category_scores_gemma":[0.00003404357,0.0002691963,0.00009103122,0.0005188335,0.00002286961,0.0004169635,0.0002076037,0.0003485019,0.0000304048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008605805,"about_ca_system_score_gemma":0.00004932776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002565837,"about_ca_topic_score_gemma":0.00001523663,"domain_scores_codex":[0.9981948,0.00006349854,0.0002894308,0.0002810185,0.0007460565,0.0004251928],"domain_scores_gemma":[0.9993377,0.00003542299,0.0000573098,0.0003720353,0.00008060791,0.0001169088],"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":[0.00001040602,0.00002039893,0.001341759,0.00008616482,0.00006396668,0.00007692286,0.0001249643,0.07314293,0.9180154,0.000003099869,0.001586367,0.005527608],"study_design_scores_gemma":[0.000931657,0.0001158314,0.0007558481,0.0001781978,0.00009227834,0.00007909034,0.0001697266,0.006143108,0.9832211,0.0003315127,0.006847526,0.001134164],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9092298,0.001572095,0.07967459,0.00004724741,0.006096391,0.0004722667,0.00003134254,0.0005687197,0.002307522],"genre_scores_gemma":[0.9982274,0.00001988808,0.0009156052,0.00005932148,0.0006315439,0.00002471868,0.000003411491,0.00008844021,0.00002967975],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08899757,"threshold_uncertainty_score":0.999976,"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."}}