{"id":"W4230175716","doi":"10.2196/preprints.8372","title":"Patterns in Patient Access and Utilization of Online Medical Records: Analysis of MyChart (Preprint)","year":2017,"lang":"en","type":"preprint","venue":"","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Login; Preprint; Medical emergency; Family medicine; World Wide Web; Computer science; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00136298,0.0001342488,0.000285291,0.003142088,0.0003835261,0.0009311714,0.000531757,0.0002674884,0.002508045],"category_scores_gemma":[0.008544597,0.0001691985,0.0007315281,0.008600878,0.0002918555,0.0006072336,0.0006890771,0.0002709533,0.0003435293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003335344,"about_ca_system_score_gemma":0.004682276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4243527,"about_ca_topic_score_gemma":0.5037556,"domain_scores_codex":[0.9983827,0.0001870811,0.0003620244,0.0002725668,0.000541417,0.0002541729],"domain_scores_gemma":[0.9891205,0.001545841,0.004973885,0.0004875385,0.003198712,0.0006735639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009456297,0.000006839407,0.996439,0.0000445652,0.00004126547,0.00002616886,0.0002112577,0.00003224097,0.00006108676,0.0000159241,0.0005696465,0.002457402],"study_design_scores_gemma":[0.000002060692,0.00001744194,0.9990999,0.0000142684,0.00001268385,0.00002762134,0.000293195,0.00009997725,0.00003021542,0.000003788386,0.0003964113,0.00000255913],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.980451,0.0004764505,0.0001349885,0.0001435714,0.000006152769,0.00004758395,0.01787098,0.00001722177,0.00085196],"genre_scores_gemma":[0.9914072,0.0003154994,0.0002503395,0.00005849887,0.00001104285,0.00005177101,0.007347731,0.00001079583,0.0005470907],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4243527,"threshold_uncertainty_score":0.8437654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1663424922897142,"score_gpt":0.5179469826804821,"score_spread":0.3516044903907679,"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."}}