{"id":"W2802458397","doi":"10.7939/r3nz8119n","title":"eHealth and mHealth Pipelines for Clinical Decision Support to Improve Medication Selection and Safety","year":2015,"lang":"en","type":"article","venue":"University of Alberta Library","topic":"Pharmaceutical Practices and Patient Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"eHealth; mHealth; Clinical decision support system; Decision support system; Selection (genetic algorithm); Computer science; Business; Medicine; Risk analysis (engineering); Health care; Nursing; Data mining; Psychological intervention; Artificial intelligence","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":[0.01012436,0.0007657555,0.0008485218,0.002931422,0.0007139018,0.004446448,0.001770707,0.001238503,0.0183917],"category_scores_gemma":[0.03093147,0.0005360906,0.001512109,0.003166592,0.0007063652,0.004976243,0.00381933,0.002254314,0.00848873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001755229,"about_ca_system_score_gemma":0.004129277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008332188,"about_ca_topic_score_gemma":0.006683243,"domain_scores_codex":[0.9950841,0.00175838,0.000652056,0.0007429172,0.001518744,0.0002437538],"domain_scores_gemma":[0.9806244,0.01078676,0.001029216,0.003037813,0.003719771,0.0008020956],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001045114,0.0003731911,0.008376111,0.001349362,0.0002996927,0.0004115956,0.001582139,0.004178062,0.007075883,0.01986952,0.1241629,0.8312764],"study_design_scores_gemma":[0.0008407334,0.00100177,0.02563642,0.002218623,0.0005286622,0.0007861082,0.002224575,0.08329733,0.0323931,0.1139343,0.736685,0.0004534156],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.04686217,0.009129669,0.7204876,0.03737261,0.002116469,0.00436834,0.0579882,0.06497813,0.05669691],"genre_scores_gemma":[0.2209901,0.007149757,0.7108395,0.006708436,0.0009332812,0.002051335,0.03043618,0.002356932,0.01853457],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.0183917,"threshold_uncertainty_score":0.06152636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0978636286759972,"score_gpt":0.3986827519806724,"score_spread":0.3008191233046752,"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."}}