{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006591763,0.0001377173,0.0003611001,0.00006281702,0.0001133085,0.000007745535,0.0001708886,0.0001043203,0.00003745236],"category_scores_gemma":[0.0008546868,0.00004844562,0.00004946784,0.0001517864,0.0001768561,0.00004746394,0.0000501944,0.0002733337,1.330876e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002022095,"about_ca_system_score_gemma":0.000123235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001218718,"about_ca_topic_score_gemma":0.00009820034,"domain_scores_codex":[0.9988267,0.0002036597,0.0003940519,0.0001885964,0.0002418609,0.0001450978],"domain_scores_gemma":[0.997263,0.001647006,0.0003916757,0.0003378588,0.0003134543,0.0000470743],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"nonrandomized_trial","study_design_scores_codex":[0.04161741,0.001076215,0.2026499,0.0002344456,0.002508776,0.0002510696,0.0040683,0.00001450896,0.06649236,0.0300845,0.008577927,0.6424246],"study_design_scores_gemma":[0.2237574,0.4100911,0.1822869,0.02319682,0.008520943,0.001217046,0.05175223,0.02042274,0.03105882,0.03174132,0.0149428,0.001011946],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9769444,0.007232325,0.001132032,0.01192127,0.001125822,0.001122397,0.0004840589,0.000005571519,0.00003214397],"genre_scores_gemma":[0.9970708,0.0002902476,0.001083439,0.0009745881,0.0001947172,0.00001488303,0.0003535002,0.00001083019,0.000007014859],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6414127,"threshold_uncertainty_score":0.1975555,"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."}}