{"id":"W4386211174","doi":"10.1109/icdh60066.2023.00027","title":"SleepSynth: Evaluating the use of Synthetic Data in Health Digital Twins","year":2023,"lang":"en","type":"article","venue":"","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Synthetic data; Machine learning; Autoencoder; Artificial intelligence; Data quality; Data mining; Data modeling; Artificial neural network","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004854694,0.0006627741,0.0004766156,0.0006446753,0.0003306053,0.0006380524,0.001007676,0.001070936,0.0007104276],"category_scores_gemma":[0.01471959,0.0001860985,0.0006771161,0.0005353143,0.0009503704,0.000789782,0.00105447,0.0008629317,0.000221368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007697858,"about_ca_system_score_gemma":0.0005979346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004743772,"about_ca_topic_score_gemma":0.004047468,"domain_scores_codex":[0.9980268,0.001218602,0.0001325721,0.0002682163,0.0002761332,0.00007764326],"domain_scores_gemma":[0.9907435,0.006778975,0.0004156465,0.0009209136,0.0008573527,0.0002836856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002146443,0.00139346,0.03478464,0.0005915363,0.00045935,0.000470676,0.0004913122,0.8603173,0.006759865,0.004721492,0.005250529,0.08261341],"study_design_scores_gemma":[0.00008858584,0.0009361751,0.007774209,0.00004767272,0.00004044033,0.0001774303,0.0002038669,0.9817585,0.005648581,0.001890894,0.001402477,0.0000311663],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9530177,0.0007512118,0.04059487,0.0007296583,0.0002154995,0.0002972668,0.002001437,0.0005644506,0.001827939],"genre_scores_gemma":[0.9745968,0.0001813266,0.02055748,0.0001831601,0.0000349764,0.0001304983,0.003675077,0.00003899132,0.0006017529],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004854694,"threshold_uncertainty_score":0.0256744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3055966267908786,"score_gpt":0.4309565075277535,"score_spread":0.1253598807368749,"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."}}