{"id":"W3155165903","doi":"10.1142/s0219519421400108","title":"PREDICTION OF SYMPTOMS PROGRESSION FOR THE PATIENTS WITH KNEE OSTEOARTHRITIS BASED ON THE QUANTITATIVE STRUCTURAL FEATURES: DATA FROM THE FNIH OA BIOMARKERS CONSORTIUM","year":2021,"lang":"en","type":"article","venue":"Journal of Mechanics in Medicine and Biology","topic":"Osteoarthritis Treatment and Mechanisms","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"WOMAC; Osteoarthritis; Support vector machine; Feature selection; Receiver operating characteristic; Naive Bayes classifier; Logistic regression; Physical therapy; Artificial intelligence; Feature (linguistics); Medicine; Random forest; Machine learning; Computer science; Physical medicine and rehabilitation; Pattern recognition (psychology); Pathology","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":[0.001474049,0.0004602835,0.0004211232,0.0008332613,0.0002371127,0.0004246048,0.0002976019,0.000419931,0.0005768618],"category_scores_gemma":[0.004597323,0.00009036419,0.0008500423,0.0006065131,0.0001429459,0.0002600981,0.0003673977,0.0004068424,0.0002034582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002537595,"about_ca_system_score_gemma":0.000364674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008294053,"about_ca_topic_score_gemma":0.01064476,"domain_scores_codex":[0.9994843,0.0001542752,0.00007665533,0.00009778034,0.0001399054,0.000047111],"domain_scores_gemma":[0.9983407,0.0006715488,0.0004315746,0.0001084569,0.0003264525,0.0001212542],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002888289,0.00008853919,0.9878526,0.00003973953,0.00008829904,0.00005396727,0.00004647423,0.001042054,0.0004148061,0.00001727365,0.0003876357,0.009679764],"study_design_scores_gemma":[0.00003070648,0.000307275,0.990011,0.00001925673,0.00008468803,0.0001991666,0.0001048816,0.008585486,0.0003031586,0.00006439525,0.0002785582,0.00001133423],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969162,0.0002972846,0.000934291,0.00008003374,0.00000774965,0.00002708241,0.001504891,0.00001320003,0.0002193118],"genre_scores_gemma":[0.9963247,0.00008660751,0.000718113,0.00001321179,0.00001028402,0.00003330265,0.002678019,0.000002130931,0.0001334407],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008294053,"threshold_uncertainty_score":0.01649153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05227197709960862,"score_gpt":0.3221021780300493,"score_spread":0.2698302009304406,"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."}}