{"id":"W4392643209","doi":"10.2147/rmhp.s451436","title":"Systematic Review and Critical Appraisal of Prediction Models for Readmission in Coronary Artery Disease Patients: Assessing Current Efficacy and Future Directions","year":2024,"lang":"en","type":"article","venue":"Risk Management and Healthcare Policy","topic":"Heart Failure Treatment and Management","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronary artery disease; Checklist; Medicine; Logistic regression; Predictive modelling; MEDLINE; CAD; Data extraction; Emergency medicine; Intensive care medicine; Internal medicine; Machine learning; Computer science; Engineering; Psychology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002762259,0.0001573159,0.0004091187,0.0003164983,0.0001083559,0.00004079205,0.0000201139,0.00003866982,0.000002136223],"category_scores_gemma":[0.0001227708,0.0001206234,0.00004681512,0.0001970789,0.0000404103,0.0002019595,0.00005425982,0.0001139615,4.931474e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007415546,"about_ca_system_score_gemma":0.00004470177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000532939,"about_ca_topic_score_gemma":0.000008347633,"domain_scores_codex":[0.9988028,0.0001034907,0.0004207084,0.0003172941,0.0001568011,0.0001988399],"domain_scores_gemma":[0.9993097,0.0001857433,0.00005362335,0.0001566954,0.00004889862,0.0002453171],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"observational","study_design_scores_codex":[0.0001098866,0.0004294219,0.01235072,0.8368803,0.0001908852,0.00001869939,0.0005853936,5.587776e-7,1.770632e-7,0.02918093,0.00192836,0.1183247],"study_design_scores_gemma":[0.006559753,0.001688758,0.5412658,0.3588123,0.01319756,0.00003503387,0.001265957,0.01669667,4.857227e-7,0.007332289,0.05250402,0.0006413669],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.05711934,0.8383774,0.001998089,0.08658142,0.0008847373,0.0140585,0.0003652892,0.0002810606,0.0003341238],"genre_scores_gemma":[0.6191797,0.3784604,0.000924587,0.000323371,0.000279138,0.0005514651,0.0001693495,0.00002816918,0.00008384625],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.5620603,"threshold_uncertainty_score":0.4918878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02780019161404486,"score_gpt":0.3869691669818102,"score_spread":0.3591689753677653,"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."}}