{"id":"W2409461510","doi":"10.1503/cmaj.1150049","title":"Polypharmacy and clinical outcomes","year":2015,"lang":"en","type":"letter","venue":"Canadian Medical Association Journal","topic":"Pharmaceutical Practices and Patient Outcomes","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Polypharmacy; Table (database); Computer science; Event (particle physics); Medicine; Data science; Data mining; Intensive care medicine","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":[0.002096904,0.0001836977,0.0005297334,0.0008825546,0.0009475044,0.001294461,0.0005827878,0.005354309,0.005222959],"category_scores_gemma":[0.03166635,0.0001389862,0.0003608024,0.00118163,0.001212469,0.001427023,0.000585061,0.006648128,0.001173312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002327056,"about_ca_system_score_gemma":0.001811077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005706476,"about_ca_topic_score_gemma":0.01099576,"domain_scores_codex":[0.9967518,0.001197027,0.0003506194,0.0003122595,0.001131158,0.0002571472],"domain_scores_gemma":[0.9818506,0.009060044,0.003175106,0.000578347,0.003001071,0.002334884],"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":[0.0002352311,0.0002009551,0.07566417,0.000356997,0.00008591101,0.003284926,0.0003697651,0.0001380305,0.0001924702,0.00759023,0.8141373,0.09774397],"study_design_scores_gemma":[0.0005415836,0.0008461148,0.3032209,0.004626764,0.0002376457,0.03684825,0.00147854,0.002706161,0.0007671978,0.07277974,0.5756103,0.0003368892],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.006665163,0.01097544,0.0001192713,0.969795,0.004325448,0.00001192099,0.0001662084,0.00002099137,0.007920524],"genre_scores_gemma":[0.2862411,0.01536396,0.0007441567,0.6030208,0.09044031,0.0000587085,0.0003311099,0.00002794245,0.003771853],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.005706476,"threshold_uncertainty_score":0.01747251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1236390446760658,"score_gpt":0.4357724743321744,"score_spread":0.3121334296561086,"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."}}