{"id":"W4394927675","doi":"10.2196/52934","title":"Data Flow Construction and Quality Evaluation of Electronic Source Data in Clinical Trials: Pilot Study Based on Hospital Electronic Medical Records in China","year":2024,"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":"Electronic data capture; Data quality; Clinical trial; Data collection; Computer science; Electronic data; Medical record; Data flow diagram; Medicine; Documentation; Data mining; Medical physics; Database; Operations management","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1026161,0.0005329194,0.001045877,0.005474267,0.001570321,0.003003659,0.001879105,0.0009853475,0.001450846],"category_scores_gemma":[0.1460335,0.0005679363,0.001625934,0.005973259,0.001817246,0.003519173,0.003100379,0.0009245071,0.0002147171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007500031,"about_ca_system_score_gemma":0.01895174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02167954,"about_ca_topic_score_gemma":0.012229,"domain_scores_codex":[0.9457995,0.02919773,0.01013829,0.003548922,0.00950021,0.001815342],"domain_scores_gemma":[0.7925358,0.1038562,0.02873965,0.01964522,0.05048142,0.004741762],"domain_codex":null,"domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002967723,0.002857541,0.7788605,0.002101902,0.0004324836,0.0006229733,0.01208061,0.005909936,0.002191436,0.00193646,0.002254947,0.1877834],"study_design_scores_gemma":[0.002020607,0.005843258,0.8994675,0.00116978,0.001254491,0.0004893158,0.01248365,0.06079439,0.007011786,0.001553339,0.007675997,0.0002358814],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9833131,0.0005902827,0.009814173,0.0007675608,0.00003873005,0.003835921,0.0008170514,0.0001389049,0.0006842608],"genre_scores_gemma":[0.9743704,0.0005337874,0.02022798,0.0002649123,0.00004722155,0.002464523,0.001749202,0.00003524677,0.0003067736],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8973839,"threshold_uncertainty_score":0.5426923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3456876116037642,"score_gpt":0.5999722839048107,"score_spread":0.2542846723010466,"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."}}