{"id":"W4221122939","doi":"10.1007/s10334-022-01004-8","title":"Investigating acute changes in osteoarthritic cartilage by integrating biomechanics and statistical shape models of bone: data from the osteoarthritis initiative","year":2022,"lang":"en","type":"article","venue":"Magnetic Resonance Materials in Physics Biology and Medicine","topic":"Osteoarthritis Treatment and Mechanisms","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; McMaster University; Hamilton Health Sciences","funders":"Institute of Musculoskeletal Health and Arthritis; Natural Sciences and Engineering Research Council of Canada; University of Waterloo; Canadian Institutes of Health Research; Mitacs; Ontario Ministry of Research, Innovation and Science; Arthritis Society","keywords":"Osteoarthritis; Cartilage; Biomechanics; Magnetic resonance imaging; Femur; Medicine; Tibia; Knee Joint; Biomedical engineering; Orthodontics; Anatomy; Pathology; Radiology; Surgery","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006294527,0.0002278273,0.0007232005,0.00006935911,0.0001211511,0.00001025568,0.0001484863,0.0000886316,0.0001783053],"category_scores_gemma":[0.0002253464,0.0001707653,0.00001087948,0.0002173312,0.0005853552,0.00007585919,0.0004449919,0.0002450733,5.268187e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002560245,"about_ca_system_score_gemma":0.00006245513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003132139,"about_ca_topic_score_gemma":0.0003576073,"domain_scores_codex":[0.9981248,0.0003723153,0.0005155327,0.0005038031,0.0001754992,0.0003080545],"domain_scores_gemma":[0.9988083,0.0005767975,0.0001615543,0.0003483239,0.00003173278,0.00007330315],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002508731,0.00007797294,0.001405623,0.00005876579,0.000008772373,0.00008285573,0.00256962,1.717512e-7,0.77004,0.00543979,0.0001137834,0.2199517],"study_design_scores_gemma":[0.0696906,0.06452323,0.006946557,0.008658534,0.001235978,0.0006692052,0.03009249,0.009116152,0.3777873,0.4250069,0.004265394,0.002007611],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9676133,0.02656925,0.00004450598,0.001242082,0.00021268,0.0006937616,0.003529645,0.00001404921,0.00008069719],"genre_scores_gemma":[0.9934856,0.002460568,0.0008564598,0.0008719575,0.0001323581,0.0001840984,0.001972192,0.00002175217,0.00001506551],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4195671,"threshold_uncertainty_score":0.6963606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03514790426452084,"score_gpt":0.2922291088110718,"score_spread":0.2570812045465509,"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."}}