{"id":"W4283215486","doi":"10.2196/39145","title":"The Power of Patient Engagement With Electronic Health Records as Research Participants","year":2022,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Digital health; Health information technology; Health care; Wearable computer; Variety (cybernetics); Wearable technology; Medicine; Patient portal; Telemedicine; Telehealth; Big data; Workflow; Data science; Internet privacy; Computer 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","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01238865,0.000124075,0.0002936258,0.0001329092,0.004751062,0.000007151564,0.0005228643,0.00009506932,0.002356468],"category_scores_gemma":[0.0005498232,0.00007829404,0.00003774264,0.0007770479,0.0002274593,0.00006498714,0.0005024777,0.003398421,0.0002008647],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008060489,"about_ca_system_score_gemma":0.01141507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003751648,"about_ca_topic_score_gemma":0.0003827921,"domain_scores_codex":[0.9915696,0.002016561,0.001819337,0.0001406999,0.002511807,0.001941965],"domain_scores_gemma":[0.9955488,0.001832471,0.000705793,0.0006824153,0.0002920091,0.0009385277],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008762823,0.0008936228,0.004687017,0.001772526,0.00007476535,0.000003768249,0.1412758,0.00003374196,8.085274e-7,0.1894173,0.4529367,0.2080277],"study_design_scores_gemma":[0.0007261263,0.002124184,0.0006173897,0.0001056156,0.00000293623,0.000003998724,0.08556867,0.000433219,0.000001830051,0.000866976,0.9094809,0.00006811017],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9115425,0.0009659891,0.0002792908,0.04277323,0.0007785949,0.0151842,0.00005755669,0.0001544348,0.02826421],"genre_scores_gemma":[0.9485999,0.001302645,0.0002048943,0.01383037,0.00007421328,0.03520348,0.00004077883,0.00002485704,0.0007188625],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4565443,"threshold_uncertainty_score":0.9989008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09704454054231565,"score_gpt":0.5092571862643248,"score_spread":0.4122126457220092,"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."}}