{"id":"W2799710455","doi":"10.1016/j.arth.2018.04.008","title":"Predictors and Cost of Readmission in Total Knee Arthroplasty","year":2018,"lang":"en","type":"article","venue":"The Journal of Arthroplasty","topic":"Total Knee Arthroplasty Outcomes","field":"Medicine","cited_by":63,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Arthritis and Musculoskeletal and Skin Diseases; National Institute on Aging; Health Services Research and Development; Orthopaedic Research and Education Foundation; Institute of Aging; National Cancer Institute; Agency for Healthcare Research and Quality; National Science Foundation; National Institutes of Health; American Cancer Society","keywords":"Medicine; Odds ratio; Confidence interval; Logistic regression; Arthroplasty; Emergency medicine; Total knee arthroplasty; Population; Knee replacement; Physical therapy; Internal medicine; Surgery; Environmental health","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001028939,0.0002253275,0.0006014202,0.0002733836,0.0001203615,0.00001230288,0.00006826429,0.0001111098,0.000336586],"category_scores_gemma":[0.0005447745,0.0001353842,0.0001224235,0.0003261039,0.0008725123,0.0002560043,0.00009110896,0.0005329585,0.0000271801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005807078,"about_ca_system_score_gemma":0.0002190828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002680551,"about_ca_topic_score_gemma":0.0001344157,"domain_scores_codex":[0.9978771,0.0001980151,0.0008848494,0.0001546711,0.0005587082,0.0003267208],"domain_scores_gemma":[0.9981565,0.0004016573,0.0005487124,0.0003191494,0.0003014771,0.0002725147],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004930867,0.000600502,0.9317157,0.0001286605,0.0002991885,0.000151972,0.006915479,0.00009804864,0.01410723,0.0001190653,0.004840643,0.03609262],"study_design_scores_gemma":[0.006353935,0.005149954,0.9650305,0.0006624864,0.0001765788,0.004698644,0.001669731,0.0002905125,0.005683048,0.00006595798,0.01003553,0.000183125],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965109,0.0004961946,0.0002534032,0.0009671735,0.0007560025,0.0003373014,0.000009713832,0.00001553237,0.0006537593],"genre_scores_gemma":[0.9979066,0.0004248138,0.0006059413,0.0001034768,0.0003500443,0.000001363665,0.000001126166,0.00002831686,0.00057834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0359095,"threshold_uncertainty_score":0.5520808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01253459741046255,"score_gpt":0.2616561375512025,"score_spread":0.2491215401407399,"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."}}