{"id":"W3097289530","doi":"10.3389/fdgth.2020.619692","title":"Advancing PPG Signal Quality and Know-How Through Knowledge Translation—From Experts to Student and Researcher","year":2020,"lang":"en","type":"article","venue":"Frontiers in Digital Health","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Institute for Health and Care Research","keywords":"Artifact (error); Quality (philosophy); Photoplethysmogram; Computer science; Pulse (music); TRACE (psycholinguistics); Wearable computer; Noise (video); SIGNAL (programming language); Medical physics; Medicine; Artificial intelligence; Computer vision; Telecommunications; Physics","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":[0.0001932921,0.0001899309,0.0003368948,0.00007367192,0.0000687662,0.0001613457,0.0001259958,0.0000621748,0.000003151031],"category_scores_gemma":[0.000103233,0.0002062698,0.00002788933,0.0002747752,0.00004778455,0.0007039048,0.00008453497,0.0002047768,0.000003232326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002769352,"about_ca_system_score_gemma":0.00005471278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006775565,"about_ca_topic_score_gemma":0.00007408227,"domain_scores_codex":[0.9985972,0.00005445603,0.0003003744,0.0003642474,0.0002328634,0.0004508592],"domain_scores_gemma":[0.999221,0.0001630082,0.0000325821,0.0001250177,0.00002855393,0.0004298094],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000152087,0.0001245367,0.3340181,0.0009614939,0.00009302134,0.00002833315,0.07427951,0.0007034522,0.00380125,0.00008181134,0.02035137,0.5654051],"study_design_scores_gemma":[0.0185429,0.005144986,0.4124691,0.005306232,0.00005854927,0.0000207045,0.2154935,0.02157476,0.03026277,0.02515257,0.2577868,0.008187111],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8086916,0.03087283,0.1532658,0.003101527,0.0006859964,0.0009194801,0.0001439748,0.0002585179,0.002060281],"genre_scores_gemma":[0.9861656,0.0004054688,0.01292746,0.000162607,0.0002348693,0.00002764277,0.00001356491,0.00004419308,0.00001855635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.557218,"threshold_uncertainty_score":0.8411439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07941163916410199,"score_gpt":0.3581418880593734,"score_spread":0.2787302488952714,"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."}}