{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002119868,0.00008811155,0.0001582121,0.0001360673,0.00009788504,0.0001842081,0.001871645,0.00002616736,0.00002135416],"category_scores_gemma":[0.002780676,0.00006029558,0.00002315987,0.001025396,0.00004014012,0.0007555892,0.001520938,0.0002265301,0.00007678383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003622835,"about_ca_system_score_gemma":0.0002174437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00173398,"about_ca_topic_score_gemma":0.0002072323,"domain_scores_codex":[0.9979951,0.0003532186,0.0004309083,0.0004302064,0.0004581581,0.0003324473],"domain_scores_gemma":[0.9959486,0.001691277,0.000146079,0.002102185,0.00004814205,0.00006370954],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000746225,0.0000748113,0.09720983,0.0002806531,0.0000144261,0.00001240404,0.003793245,0.02517627,0.00002052666,0.02726533,0.00404098,0.8421041],"study_design_scores_gemma":[0.00006779551,0.00008932933,0.02864644,0.00007623283,5.607998e-7,0.000005017281,0.00005615079,0.9680306,0.000003131024,0.0004723509,0.002490849,0.00006152954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6186692,0.00027469,0.2107971,0.1622195,0.001469459,0.001936227,0.000128364,0.001609458,0.002896015],"genre_scores_gemma":[0.9839939,0.00001284722,0.01493907,0.000595213,0.00002490383,0.000007497943,0.00001954858,0.00001076669,0.0003962149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9428543,"threshold_uncertainty_score":0.3478013,"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."}}