{"id":"W2416365720","doi":"10.2196/resprot.5543","title":"Using an Electronic Decision Support Tool to Reduce Inappropriate Polypharmacy and Optimize Medicines: Rationale and Methods","year":2016,"lang":"en","type":"article","venue":"JMIR Research Protocols","topic":"Pharmaceutical Practices and Patient Outcomes","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Polypharmacy; Psychological intervention; Clinical decision support system; Medicine; Decision support system; Electronic prescribing; Harm; Pharmacy; Health care; Family medicine; Nursing; Intensive care medicine; Psychology; Computer science; Data mining","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":[0.02604069,0.002034741,0.0009467693,0.004154513,0.0009634959,0.002828168,0.002774999,0.002568189,0.00591966],"category_scores_gemma":[0.04294928,0.0009376554,0.001533106,0.00246554,0.002343021,0.004289405,0.001839746,0.001542249,0.001152193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001996874,"about_ca_system_score_gemma":0.007102388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009041288,"about_ca_topic_score_gemma":0.001215379,"domain_scores_codex":[0.9760534,0.01578804,0.00232063,0.001441217,0.004108003,0.0002887797],"domain_scores_gemma":[0.9626048,0.02766152,0.002687987,0.001501188,0.004834721,0.0007098482],"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":[0.002936336,0.009278996,0.02451805,0.01506026,0.0004148943,0.0003729972,0.001502181,0.004999346,0.004136066,0.03237193,0.006535052,0.8978738],"study_design_scores_gemma":[0.02975915,0.04879997,0.0747612,0.03764766,0.005194674,0.005785736,0.004530586,0.2771906,0.1043797,0.1366328,0.2729254,0.002392584],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"protocol","genre_scores_codex":[0.06320542,0.01093042,0.7735497,0.01276234,0.0009187071,0.1168102,0.002544962,0.001443716,0.01783452],"genre_scores_gemma":[0.09921359,0.003209977,0.8494188,0.00150229,0.0002248653,0.04402811,0.0004788935,0.00004950869,0.001874022],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.02604069,"threshold_uncertainty_score":0.137718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5275342937475006,"score_gpt":0.674895320598933,"score_spread":0.1473610268514324,"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."}}