{"id":"W3095155567","doi":"10.1016/j.berh.2020.101598","title":"Clinical advances – from bench to bedside","year":2020,"lang":"en","type":"review","venue":"Best Practice & Research Clinical Rheumatology","topic":"Cardiac, Anesthesia and Surgical Outcomes","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Bench to bedside; Medical physics; Medicine; 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":[0.00345013,0.001351833,0.002519494,0.004358724,0.000425273,0.002948707,0.001140259,0.002404072,0.0102335],"category_scores_gemma":[0.007155678,0.000542665,0.0009210663,0.003716505,0.001164509,0.003378327,0.001950262,0.003807434,0.002287222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001905367,"about_ca_system_score_gemma":0.005470569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001864908,"about_ca_topic_score_gemma":0.006319405,"domain_scores_codex":[0.9985577,0.0004010303,0.0003044922,0.0001730177,0.0004491309,0.0001145748],"domain_scores_gemma":[0.9955589,0.002651833,0.0006868833,0.00009268165,0.0007341255,0.0002754762],"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":[0.00008157844,0.00006208925,0.0002452457,0.04380706,0.0001895663,0.00008664672,0.00008517064,0.0001867857,0.0003057111,0.004714206,0.05924039,0.8909956],"study_design_scores_gemma":[0.00009050652,0.0001325205,0.001116768,0.06225992,0.000526615,0.0005266469,0.0001773475,0.00009750361,0.00013105,0.005332631,0.9295782,0.00003022699],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00003211621,0.9973598,0.00005264851,0.001309539,0.000558875,0.000004305552,0.00001368104,0.000006128352,0.0006628804],"genre_scores_gemma":[0.0005821236,0.9957885,0.0002076391,0.001988383,0.001054476,0.00001001455,0.00002192325,0.000001962465,0.0003449848],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.0102335,"threshold_uncertainty_score":0.03423446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3275694723249054,"score_gpt":0.626421518481319,"score_spread":0.2988520461564136,"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."}}