{"id":"W2529830112","doi":"10.1016/j.joca.2016.09.015","title":"Cluster analysis of quantitative MRI T2 and T1 relaxation times of cartilage identifies differences between healthy and ACL-injured individuals at 3T","year":2016,"lang":"en","type":"article","venue":"Osteoarthritis and Cartilage","topic":"Osteoarthritis Treatment and Mechanisms","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Arthritis and Musculoskeletal and Skin Diseases; GE Healthcare; National Institutes of Health; Arthritis Foundation","keywords":"Medicine; Cartilage; Cartilage damage; Knee cartilage; Magnetic resonance imaging; Nuclear medicine; Osteoarthritis; Articular cartilage; Mann–Whitney U test; Anatomy; Pathology; Internal medicine; Radiology","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":[0.0008433544,0.0004131534,0.0004882363,0.001610247,0.000640523,0.0007236797,0.000397483,0.0003686592,0.001955622],"category_scores_gemma":[0.001585791,0.0001996754,0.0005605486,0.0008430085,0.0004087412,0.0004054255,0.0005496172,0.0002909054,0.000339334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003173675,"about_ca_system_score_gemma":0.0005797399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005991824,"about_ca_topic_score_gemma":0.009737603,"domain_scores_codex":[0.9997252,0.00003455174,0.00002125026,0.00008844073,0.00006622029,0.00006432721],"domain_scores_gemma":[0.9993231,0.0001424574,0.0001252389,0.00009071767,0.000241665,0.00007677259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.008510264,0.0004090433,0.1361973,0.0007056565,0.001382861,0.0005983018,0.004574534,0.00393176,0.6904151,0.00140676,0.004691467,0.147177],"study_design_scores_gemma":[0.0000968671,0.0008181831,0.9432101,0.00004941932,0.0004953461,0.000975589,0.001511917,0.0105678,0.0372568,0.001959094,0.00293487,0.0001239556],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9838545,0.0003669906,0.0132914,0.0001078436,0.0000338562,0.00007841553,0.0007134633,0.0002647893,0.001288758],"genre_scores_gemma":[0.9885731,0.0001508078,0.009110404,0.00003550665,0.00002114132,0.0001022263,0.0007632171,0.0001469243,0.001096806],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005991824,"threshold_uncertainty_score":0.0119139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01660723921317282,"score_gpt":0.2704480172016493,"score_spread":0.2538407779884765,"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."}}