{"id":"W4400539243","doi":"10.2196/56872","title":"User Requirements for an Electronic Patient Recruitment System: Semistructured Interview Analysis After First Implementation in 3 German University Hospitals","year":2024,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Workflow; German; Informatics; Health informatics; Medical education; Medicine; Computer science; Nursing; Engineering; Public health; Database","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":[0.04554718,0.0009007913,0.0007765886,0.001885383,0.004211131,0.002889448,0.001524001,0.001811139,0.001367679],"category_scores_gemma":[0.06533144,0.0009792999,0.0007789031,0.001204852,0.004410214,0.002420134,0.00414791,0.002477238,0.0004013498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008310695,"about_ca_system_score_gemma":0.004848298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00449458,"about_ca_topic_score_gemma":0.006064304,"domain_scores_codex":[0.9635739,0.02731545,0.001965054,0.001551634,0.002500475,0.003093646],"domain_scores_gemma":[0.8820364,0.09709912,0.005521058,0.001974019,0.009909688,0.003459726],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002031911,0.0003758641,0.01480753,0.0003238084,0.000009776881,0.001063783,0.9660846,0.0003184054,0.005209488,0.0003530108,0.0004175712,0.01083302],"study_design_scores_gemma":[0.00004243512,0.0009827367,0.02472194,0.0003026733,0.0000198649,0.0003769545,0.9599224,0.001730943,0.00590952,0.0002894725,0.005601628,0.00009937682],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954796,0.00004442419,0.00291764,0.0002876685,0.000007662788,0.0005290157,0.00008000915,0.00002105159,0.0006328774],"genre_scores_gemma":[0.9913909,0.000113018,0.005866065,0.0003171839,0.00000919792,0.001403821,0.0001420471,0.00003314776,0.000724639],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04554718,"threshold_uncertainty_score":0.2408794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08343907060782084,"score_gpt":0.4687128806905547,"score_spread":0.3852738100827339,"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."}}