{"id":"W2936693169","doi":"10.2196/10832","title":"Structure and Content of Drug Monitoring Advices Included in Discharge Letters at Interfaces of Care: Exploratory Analysis Preceding Database Development","year":2019,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Pharmaceutical Practices and Patient Outcomes","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Database; Content analysis; World Wide Web","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":[0.01476306,0.0003245534,0.0007243248,0.01077013,0.0005892091,0.002399264,0.0009720748,0.0005686696,0.001685418],"category_scores_gemma":[0.1087463,0.0003232987,0.001179335,0.01165249,0.0005182492,0.001374218,0.001964472,0.0005224422,0.0004352406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001914314,"about_ca_system_score_gemma":0.0031728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003711934,"about_ca_topic_score_gemma":0.003351479,"domain_scores_codex":[0.9758464,0.01134594,0.00626164,0.002067225,0.003722232,0.0007564881],"domain_scores_gemma":[0.8213811,0.1313629,0.02428094,0.007420849,0.01415162,0.001402609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.00139457,0.0006394319,0.8568056,0.002167075,0.0003273954,0.0004040259,0.01663218,0.0006193888,0.002809626,0.0006937473,0.001388277,0.1161188],"study_design_scores_gemma":[0.0001082585,0.0007022159,0.9747143,0.0003698199,0.0003514183,0.0004066262,0.01065595,0.004359048,0.003019165,0.0003727542,0.004882831,0.00005746806],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9872462,0.0004074439,0.003607184,0.0001356561,0.000006213061,0.0008970445,0.006277478,0.0001023544,0.001320383],"genre_scores_gemma":[0.9665739,0.0002781987,0.01939126,0.00006566902,0.00001209344,0.001450996,0.01161695,0.00003367837,0.0005772394],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01476306,"threshold_uncertainty_score":0.07807547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06434978772911353,"score_gpt":0.3664407345971833,"score_spread":0.3020909468680698,"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."}}