{"id":"W2005968288","doi":"10.1016/s1526-4114(07)60198-x","title":"EMR Systems Face Hurdles Especially in Geriatrics","year":2007,"lang":"en","type":"article","venue":"Caring for the Ages","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Pharmacy; Geriatrics; Medical record; Face (sociological concept); Quarter (Canadian coin); Business; Medicine; Family medicine; History; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.02304282,0.0005044852,0.0006229437,0.001735979,0.005465665,0.00679419,0.002362039,0.006412465,0.04186265],"category_scores_gemma":[0.09434598,0.0006646918,0.0008578451,0.001729353,0.001445779,0.008405757,0.005261109,0.005505954,0.01396785],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002242272,"about_ca_system_score_gemma":0.006507223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00468499,"about_ca_topic_score_gemma":0.0130468,"domain_scores_codex":[0.9848263,0.005284396,0.001574316,0.0009458935,0.004350529,0.003018528],"domain_scores_gemma":[0.9038297,0.03023839,0.01380416,0.005990008,0.02098439,0.02515333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005842728,0.000848192,0.1484219,0.0009983588,0.0002010478,0.007291348,0.006759159,0.001472045,0.001445075,0.007791657,0.482314,0.341873],"study_design_scores_gemma":[0.0002078856,0.001388165,0.1903368,0.002753165,0.0002517182,0.0183432,0.05002186,0.002828518,0.001529015,0.02287517,0.7091134,0.0003511224],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.1437168,0.008587488,0.01270224,0.7142652,0.009112665,0.0003628522,0.001693223,0.002186901,0.1073726],"genre_scores_gemma":[0.7014418,0.008954852,0.0308944,0.193395,0.01625331,0.0005516406,0.001686918,0.0007744303,0.0460476],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.04186265,"threshold_uncertainty_score":0.1400445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08933390411368415,"score_gpt":0.4412923288046466,"score_spread":0.3519584246909625,"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."}}