{"id":"W4221046585","doi":"10.1016/j.arth.2022.02.104","title":"Corrigendum to “Logistic Regression and Machine Learning Models Cannot Discriminate Between Satisfied and Dissatisfied Total Knee Arthroplasty Patients [The Journal of Arthroplasty 37 (2022) 267-273]","year":2022,"lang":"en","type":"erratum","venue":"The Journal of Arthroplasty","topic":"Total Knee Arthroplasty Outcomes","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"London Health Sciences Centre; Western University","funders":"","keywords":"Logistic regression; Medicine; Total knee arthroplasty; Arthroplasty; Physical therapy; Machine learning; Surgery; Internal 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":[0.004942312,0.002323274,0.002809973,0.00361595,0.003983501,0.004326656,0.003658738,0.0100712,0.0411762],"category_scores_gemma":[0.05984434,0.001665793,0.003331417,0.002687387,0.002160878,0.00182634,0.002125325,0.01190927,0.02566432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00461671,"about_ca_system_score_gemma":0.007466285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08388019,"about_ca_topic_score_gemma":0.1082318,"domain_scores_codex":[0.9950059,0.0009349608,0.001150415,0.0006378789,0.001759402,0.0005114714],"domain_scores_gemma":[0.9685835,0.009493425,0.001293947,0.001375378,0.01820969,0.001044068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001096164,0.000005413031,0.00006922214,0.00003080535,0.000008362641,0.0001099687,0.00001070183,0.00001841346,0.00001227192,0.0001617186,0.9978975,0.00166455],"study_design_scores_gemma":[0.00007154109,0.00005035292,0.003270488,0.0003759578,0.0001139338,0.0005784399,0.0001445465,0.0005721888,0.000277314,0.001392678,0.9930728,0.00007979029],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0001083818,0.0009069724,0.000258528,0.0873603,0.9085356,0.00002558554,0.0004866594,0.0001559196,0.002162134],"genre_scores_gemma":[0.008393311,0.007213556,0.002317298,0.3268811,0.4652082,0.0002250637,0.001901194,0.0006187084,0.1872415],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.08388019,"threshold_uncertainty_score":0.1667839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03797902543169256,"score_gpt":0.2648669674557566,"score_spread":0.226887942024064,"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."}}