{"id":"W4388483017","doi":"10.2196/51388","title":"Enriching Data Science and Health Care Education: Application and Impact of Synthetic Data Sets Through the Health Gym Project","year":2023,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Wellcome Trust","keywords":"Health care; Data science; Health science; Computer science; Psychology; Medical education; Medicine; Political science","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.005991057,0.0001557788,0.0002850846,0.000198332,0.001826052,0.00003271134,0.001315936,0.0001362334,0.00004958385],"category_scores_gemma":[0.004115797,0.0001093044,0.0000150296,0.001563541,0.0006007925,0.00075641,0.00102674,0.000666119,0.0000314631],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006661533,"about_ca_system_score_gemma":0.07053696,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04095868,"about_ca_topic_score_gemma":0.003324628,"domain_scores_codex":[0.9961346,0.0006448997,0.0008559088,0.000824246,0.0009752914,0.0005650865],"domain_scores_gemma":[0.9955506,0.000684516,0.00058639,0.002190745,0.0005795485,0.0004082444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001686649,0.0001672571,0.02203659,0.001652631,0.000008542492,9.7291e-8,0.09182086,6.228141e-7,0.000008234888,0.00312364,0.1077666,0.773398],"study_design_scores_gemma":[0.0003270327,0.000646909,0.3064711,0.004048423,0.00003738687,0.00004319333,0.5201276,0.04504751,0.000007275441,0.005487601,0.1172089,0.0005470501],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6243781,0.01162759,0.0005796169,0.345814,0.003223033,0.01214163,0.0004997176,0.0003150141,0.001421293],"genre_scores_gemma":[0.990221,0.002018818,0.0005629573,0.004859484,0.0005405803,0.0005706588,0.001164609,0.00002438427,0.00003747731],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.772851,"threshold_uncertainty_score":0.9994735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2861359864077737,"score_gpt":0.6359624549223465,"score_spread":0.3498264685145728,"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."}}