{"id":"W4399761240","doi":"10.1016/j.atssr.2024.06.001","title":"Artificial Intelligence to Enhance Readability of Cardiac Surgery Patient Education Material","year":2024,"lang":"en","type":"article","venue":"Annals of Thoracic Surgery Short Reports","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Readability; Cardiac surgery; Medicine; Psychology; Computer science; Cardiology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"bench_or_experimental","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"design_other","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"medium","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001768721,0.0003402326,0.0002858445,0.0009219254,0.0001764644,0.001847006,0.0003420336,0.0003849794,0.008679649],"category_scores_gemma":[0.02661649,0.00007615293,0.0003918802,0.0004709966,0.0001775288,0.001366924,0.0007319417,0.0005944272,0.001312589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002928623,"about_ca_system_score_gemma":0.0002951495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000465202,"about_ca_topic_score_gemma":0.0008117077,"domain_scores_codex":[0.9990103,0.0004284363,0.00009924578,0.00008716497,0.0003124008,0.00006251508],"domain_scores_gemma":[0.9847505,0.01207636,0.001060389,0.0004301171,0.00126456,0.0004180753],"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":[0.00111589,0.001972367,0.0197636,0.001314481,0.000118553,0.0003075171,0.001818511,0.00248727,0.01353682,0.0009756066,0.01297129,0.9436181],"study_design_scores_gemma":[0.0009926016,0.01979105,0.4955194,0.003306284,0.001390008,0.004203886,0.005795896,0.07659805,0.180982,0.03316803,0.1777086,0.0005442692],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9087189,0.00591793,0.03317199,0.006524497,0.001043287,0.0005042765,0.0009284909,0.001981729,0.04120886],"genre_scores_gemma":[0.948552,0.001958189,0.0407653,0.001238417,0.0003949873,0.0001679136,0.0008496453,0.0002009824,0.005872443],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008679649,"threshold_uncertainty_score":0.02903634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.200493349871075,"score_gpt":0.4905908077689833,"score_spread":0.2900974578979083,"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."}}