{"id":"W3197829494","doi":"10.1186/s42836-021-00087-3","title":"Development and internal validation of machine learning algorithms to predict patient satisfaction after total hip arthroplasty","year":2021,"lang":"en","type":"article","venue":"Arthroplasty","topic":"Total Knee Arthroplasty Outcomes","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"WOMAC; Medicine; Physical therapy; Algorithm; Patient satisfaction; Discriminative model; Machine learning; Logistic regression; Arthroplasty; Osteoarthritis; Artificial intelligence; Surgery; Computer science; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02155422,0.001047684,0.000760783,0.001560559,0.0004867054,0.001205561,0.001015373,0.0009592203,0.0007431128],"category_scores_gemma":[0.04038364,0.0003049774,0.0009984367,0.0007981159,0.0005455127,0.0006983348,0.001011226,0.001298829,0.0004373334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006631906,"about_ca_system_score_gemma":0.001489814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001875041,"about_ca_topic_score_gemma":0.0008585471,"domain_scores_codex":[0.9941215,0.003893649,0.0005143442,0.000604298,0.0006431817,0.0002230278],"domain_scores_gemma":[0.9680837,0.02258105,0.00192655,0.00172499,0.005288234,0.0003955418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001193179,0.001336107,0.4479589,0.0001983292,0.001016442,0.00009820469,0.0002156566,0.3218281,0.002461422,0.0007190954,0.002264283,0.2207103],"study_design_scores_gemma":[0.0000494953,0.0004242338,0.02326095,0.00003318045,0.00005291805,0.00004850035,0.00003741949,0.9737838,0.001598726,0.0004719315,0.0002266013,0.00001219554],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.86198,0.0006649728,0.1332816,0.000327282,0.00009140277,0.0003923287,0.0007916593,0.0009799425,0.001490762],"genre_scores_gemma":[0.9656749,0.00008117353,0.03236651,0.00006727251,0.00002913729,0.0002326569,0.00134879,0.00002732537,0.0001723009],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02155422,"threshold_uncertainty_score":0.113991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009436733506694132,"score_gpt":0.2330165249057404,"score_spread":0.2235797913990462,"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."}}