{"id":"W4383219075","doi":"10.1109/dsp58604.2023.10167869","title":"Improving PPG Signal Classification with Machine Learning: The Power of a Second Opinion","year":2023,"lang":"en","type":"article","venue":"","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Photoplethysmogram; Computer science; Artificial intelligence; Machine learning; Probabilistic logic; Bayesian probability; Bayesian optimization; SIGNAL (programming language); Pattern recognition (psychology); Computer vision","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001657755,0.0001010704,0.00009143113,0.00007884963,0.00005744293,0.00002397779,0.0001156832,0.00003880762,0.0001765122],"category_scores_gemma":[0.00002038777,0.00006703247,0.00002919604,0.0003405147,0.0000276054,0.0001105897,0.00003153028,0.0001803416,0.00005032755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003222628,"about_ca_system_score_gemma":0.00001225714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002722264,"about_ca_topic_score_gemma":0.00001783769,"domain_scores_codex":[0.9994034,0.00002008231,0.0001406743,0.0001151794,0.0001533226,0.00016735],"domain_scores_gemma":[0.9996329,0.000110691,0.00003827394,0.0001494114,0.00003608984,0.00003262456],"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":[0.00001151202,0.000007240295,0.01493917,0.00008453512,0.00003915484,0.00000192638,0.0004547012,0.006194063,0.974019,0.0003654333,0.0002892494,0.003594046],"study_design_scores_gemma":[0.001224359,0.0005746076,0.08599755,0.0001694729,0.00003092538,0.00002198876,0.003634354,0.1690274,0.7301763,0.000242879,0.008140627,0.0007595491],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9543903,0.0001945793,0.02821346,0.0001052263,0.0004711614,0.0003354488,0.000008258222,0.0009117621,0.01536975],"genre_scores_gemma":[0.9990861,0.00001047142,0.000332005,0.000004681471,0.00007263396,0.00001729373,0.000009990593,0.00003325544,0.0004336046],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2438427,"threshold_uncertainty_score":0.2733505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01602112685949411,"score_gpt":0.2200923186603775,"score_spread":0.2040711918008833,"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."}}