{"id":"W4416050804","doi":"10.17615/vkfe-hd87","title":"Precision Medicine-Based Machine Learning Analyses to Explore Optimal Exercise Therapies for Individuals With Knee Osteoarthritis: Random Forest-Informed Tree-Based Learning.","year":2025,"lang":"en","type":"article","venue":"UNC Libraries","topic":"Osteoarthritis Treatment and Mechanisms","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"WOMAC; Osteoarthritis; Body mass index; MEDLINE","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000275481,0.0005511774,0.001103989,0.0008601393,0.0005039266,0.0001956373,0.0001935542,0.0002004867,0.0002189817],"category_scores_gemma":[0.0007494678,0.0003799934,0.0002498293,0.0007458361,0.0002461121,0.0004698579,0.00006435288,0.0003251914,0.00001377494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005599526,"about_ca_system_score_gemma":0.0006231873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002523297,"about_ca_topic_score_gemma":0.00009203044,"domain_scores_codex":[0.997535,0.0001063665,0.0005960147,0.0005811984,0.0005853944,0.0005960184],"domain_scores_gemma":[0.9977542,0.001146625,0.000206668,0.0004049862,0.0002049687,0.0002826116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"randomized_trial","study_design_scores_codex":[0.07761977,0.0006093632,0.1771612,0.001082113,0.0009313548,0.0001756921,0.01205911,0.01174748,0.003686393,0.004922564,0.003049623,0.7069553],"study_design_scores_gemma":[0.3705316,0.1302283,0.006608335,0.02473855,0.005863285,0.00003125723,0.02417477,0.01004802,0.2128663,0.006933155,0.2052213,0.002755213],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8781431,0.01771927,0.08342538,0.00627096,0.0005299906,0.00929192,0.00008644126,0.001484848,0.003048069],"genre_scores_gemma":[0.8489457,0.00005775086,0.1369126,0.001490535,0.0002263249,0.002376212,0.002144367,0.0001502869,0.007696233],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7042001,"threshold_uncertainty_score":0.9998652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03274677144806609,"score_gpt":0.2980500291267078,"score_spread":0.2653032576786417,"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."}}