{"id":"W4320026948","doi":"10.2196/44784","title":"Integrated Personal Health Record in Indonesia: Design Science Research Study","year":2023,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Architecture; Stakeholder; eHealth; Knowledge management; Computer science; Health care; Business; Public relations; Geography; Economic growth","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0298967,0.0005756596,0.0008725691,0.002235789,0.001855698,0.003800542,0.001093663,0.0009928856,0.003090661],"category_scores_gemma":[0.0236327,0.0005172853,0.000799941,0.002415678,0.001788459,0.002127258,0.001766386,0.001355157,0.0004522564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006413564,"about_ca_system_score_gemma":0.009083604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002047452,"about_ca_topic_score_gemma":0.00284434,"domain_scores_codex":[0.9702373,0.0218359,0.00208497,0.001627438,0.003327753,0.0008865367],"domain_scores_gemma":[0.9598868,0.02801548,0.003021164,0.002477505,0.005652324,0.0009467698],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"design_other","study_design_scores_codex":[0.001870149,0.01948669,0.1320908,0.02283881,0.0006216061,0.003867064,0.1458536,0.02280498,0.01794994,0.0507872,0.004337067,0.577492],"study_design_scores_gemma":[0.003630276,0.03760056,0.2105702,0.01733648,0.003318413,0.004921335,0.3205676,0.1040791,0.05247078,0.03717052,0.2076922,0.0006425364],"study_design_candidate":"design_other","study_design_consensus":"design_other","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8598239,0.002614026,0.08034375,0.001213735,0.00009192034,0.01980892,0.0004720305,0.0001339719,0.03549775],"genre_scores_gemma":[0.8686276,0.00171673,0.1131336,0.0004787942,0.00002827593,0.01272669,0.0002252923,0.00003736141,0.003025738],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0298967,"threshold_uncertainty_score":0.1581107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2758391536955674,"score_gpt":0.5650288364438233,"score_spread":0.2891896827482558,"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."}}