{"id":"W1483935724","doi":"","title":"The role of the electronic medical record in the assessment of health related quality of life.","year":2011,"lang":"en","type":"article","venue":"PubMed","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Nutrition, Metabolism and Diabetes","funders":"","keywords":"Medicine; Cohort; Medical record; Artificial intelligence; Depression (economics); Quality of life (healthcare); Anxiety; Health care; Electronic health record; Health records; Electronic medical record; Machine learning; Physical therapy; Computer science; Emergency medicine; Internal medicine; Psychiatry; Nursing","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":[0.01366861,0.0002772802,0.0005070915,0.004161973,0.0003273492,0.002163529,0.0007247684,0.0004255451,0.001979754],"category_scores_gemma":[0.0525597,0.000156852,0.0003360589,0.00478549,0.0004571634,0.002635819,0.0009985955,0.0006622425,0.0006275588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006456896,"about_ca_system_score_gemma":0.001109917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002822116,"about_ca_topic_score_gemma":0.002989001,"domain_scores_codex":[0.9869918,0.009001654,0.00119327,0.0006120386,0.002071745,0.0001295153],"domain_scores_gemma":[0.9175332,0.05880072,0.01002233,0.005742027,0.006948556,0.0009530372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003693991,0.0001305639,0.386076,0.00116994,0.0003766374,0.0001581261,0.0003687409,0.0005262775,0.0006194341,0.002828796,0.01326645,0.5941095],"study_design_scores_gemma":[0.0001607742,0.001139828,0.8555894,0.003736357,0.0008071269,0.002640715,0.001662273,0.01626487,0.003296675,0.01126974,0.1033104,0.0001219337],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5556566,0.2010033,0.07862589,0.03796364,0.002807087,0.000838993,0.05404732,0.0008457866,0.06821135],"genre_scores_gemma":[0.9193593,0.0195188,0.0475105,0.002589629,0.001193212,0.0003290217,0.007712252,0.00005392848,0.001733364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01366861,"threshold_uncertainty_score":0.07228738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07122997294335062,"score_gpt":0.336008009801487,"score_spread":0.2647780368581364,"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."}}