{"id":"W2315912864","doi":"10.1016/s0735-1097(16)30804-x","title":"MULTI-FACETED KNOWLEDGE TRANSLATION TO IMPROVE CARE OF PATIENTS WITH ATRIAL FIBRILLATION: PRELIMINARY RESULTS FROM THE INTEGRATE/FACILITER PROJECTS","year":2016,"lang":"en","type":"article","venue":"Journal of the American College of Cardiology","topic":"Text Readability and Simplification","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University Health Centre","funders":"","keywords":"Medicine; Atrial fibrillation; Translation (biology); Intensive care medicine; Knowledge translation; Internal medicine; Knowledge management; Computer science","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":[0.01966585,0.000907787,0.001102878,0.001297488,0.001632234,0.002477525,0.001710497,0.00136971,0.006817417],"category_scores_gemma":[0.06708754,0.0003864548,0.001414359,0.001174005,0.00114052,0.002196079,0.006032796,0.002180868,0.001059948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001577374,"about_ca_system_score_gemma":0.009804635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005898963,"about_ca_topic_score_gemma":0.008079295,"domain_scores_codex":[0.988673,0.007871254,0.0008645314,0.0008770646,0.00119058,0.0005235513],"domain_scores_gemma":[0.9252719,0.05945019,0.002188475,0.004638687,0.005224214,0.003226642],"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":[0.003823094,0.02584325,0.01446174,0.003517954,0.0004212029,0.0008363799,0.03786162,0.004624789,0.005059486,0.0008580116,0.01008828,0.8926042],"study_design_scores_gemma":[0.03633245,0.09516926,0.2982098,0.009474017,0.009058959,0.005933808,0.1073886,0.1404873,0.1057083,0.03462653,0.155238,0.002373079],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9495777,0.0005933557,0.02820409,0.002702097,0.0001790675,0.007375395,0.0020503,0.00156377,0.007754241],"genre_scores_gemma":[0.7434791,0.001037673,0.2391577,0.001224917,0.0001115339,0.006283788,0.003524699,0.0003686784,0.004812077],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01966585,"threshold_uncertainty_score":0.1040042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02291550618767262,"score_gpt":0.2573712624807077,"score_spread":0.2344557562930351,"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."}}