{"id":"W4394685747","doi":"10.2196/51171","title":"Scalable Approach to Consumer Wearable Postmarket Surveillance: Development and Validation Study","year":2024,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Wearable computer; Computer science; Classifier (UML); Heuristics; Wearable technology; Health care; Scalability; Artificial intelligence; Medicine; Machine learning; Database","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005007552,0.000846642,0.0004921882,0.0007241892,0.0002493621,0.00054289,0.001897867,0.0007765094,0.001764796],"category_scores_gemma":[0.008544726,0.0002551509,0.0005325192,0.0006500407,0.0004380272,0.0009543942,0.0009445912,0.000928039,0.0008663809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001172234,"about_ca_system_score_gemma":0.001320704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01040626,"about_ca_topic_score_gemma":0.008507397,"domain_scores_codex":[0.9976547,0.0009626276,0.0001410994,0.0004365142,0.0006584062,0.0001467322],"domain_scores_gemma":[0.9946846,0.001810129,0.0003644589,0.0009700867,0.001879339,0.000291332],"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":[0.002412888,0.009430598,0.08198343,0.0009658958,0.0004994891,0.001065131,0.001126508,0.1757709,0.03944106,0.003548679,0.02138562,0.6623698],"study_design_scores_gemma":[0.0004356196,0.002324194,0.03323705,0.00009750357,0.00008439413,0.0002837176,0.0004215254,0.9424963,0.01265377,0.001162857,0.006764098,0.00003899151],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8646569,0.0005961638,0.121679,0.0004402429,0.0001450793,0.002128102,0.001774554,0.004165474,0.004414367],"genre_scores_gemma":[0.8258733,0.0002917219,0.1656669,0.0001551758,0.00002990133,0.0009299734,0.004082014,0.0001164197,0.002854544],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01040626,"threshold_uncertainty_score":0.02648276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02131183582894062,"score_gpt":0.3106476637259067,"score_spread":0.289335827896966,"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."}}