{"id":"W4412370635","doi":"10.29303/jppipa.v11i6.11081","title":"Analysis of Electronic Medical Records Data Security: Case Study in Citra Husada Sigli Hospital","year":2025,"lang":"en","type":"article","venue":"Jurnal Penelitian Pendidikan IPA","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital","funders":"","keywords":"Medical record; Medical emergency; Medicine; Radiology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003308743,0.0003467836,0.0003300945,0.00164038,0.005858397,0.002442647,0.00120969,0.002119785,0.002591109],"category_scores_gemma":[0.00756869,0.0003930003,0.0004669346,0.001838875,0.002369928,0.001685718,0.002403127,0.001775698,0.0003459179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004461627,"about_ca_system_score_gemma":0.003316171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005526057,"about_ca_topic_score_gemma":0.01246594,"domain_scores_codex":[0.9943505,0.003190211,0.0002794059,0.0003483611,0.000994548,0.0008370208],"domain_scores_gemma":[0.9928706,0.003842932,0.001227233,0.000208156,0.0008570853,0.0009939955],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.000202278,0.00132973,0.1293888,0.001367605,0.00007246249,0.1728072,0.6239365,0.0005638862,0.003305729,0.006922925,0.008317185,0.05178586],"study_design_scores_gemma":[0.000009566374,0.0003560804,0.03800353,0.0004348354,0.00002935896,0.03863648,0.8912308,0.0006649185,0.002079023,0.000678156,0.02782242,0.00005486106],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902382,0.0007945348,0.001249216,0.003158108,0.00003798101,0.0001505562,0.00007387935,0.00001146573,0.004286034],"genre_scores_gemma":[0.9918686,0.001695544,0.00147998,0.000758839,0.00003754554,0.00006299422,0.00004941956,0.00001297052,0.004034038],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005858397,"threshold_uncertainty_score":0.03237158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0939730511670279,"score_gpt":0.4969199667257233,"score_spread":0.4029469155586954,"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."}}