{"id":"W1993711449","doi":"10.1016/j.medengphy.2010.06.002","title":"Diffusion coefficients of articular cartilage for different CT and MRI contrast agents","year":2010,"lang":"en","type":"article","venue":"Medical Engineering & Physics","topic":"Osteoarthritis Treatment and Mechanisms","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Sigrid Juséliuksen Säätiö","keywords":"Cartilage; Gadodiamide; Magnetic resonance imaging; Diffusion; Biomedical engineering; Effective diffusion coefficient; Osteoarthritis; Contrast (vision); Articular cartilage; Diffusion MRI; Chemistry; Materials science; Nuclear magnetic resonance; Anatomy; Medicine; Pathology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007341596,0.0001347198,0.0002885854,0.00002451985,0.00002728588,0.000006074288,0.00004358577,0.00004848196,0.00003304648],"category_scores_gemma":[0.0001257894,0.0001049312,0.00007891496,0.00004826839,0.00004519511,0.0000215253,0.00003155714,0.0001486572,0.000002066076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001020973,"about_ca_system_score_gemma":0.00001878054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002017657,"about_ca_topic_score_gemma":0.000002027288,"domain_scores_codex":[0.9991271,0.000004293481,0.0001756201,0.0001573752,0.0003276251,0.0002079736],"domain_scores_gemma":[0.9994621,0.00006153258,0.00003181188,0.0001480883,0.00003587639,0.0002605436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008486641,0.0009206871,0.001892661,0.0003857464,0.00005945058,0.00009667048,0.0002262507,0.00003908802,0.9346364,0.003872027,0.00009924841,0.05768694],"study_design_scores_gemma":[0.01463114,0.001784948,0.005296575,0.0007129725,0.0004145081,0.00008733607,0.00004119208,0.08867402,0.8827496,0.0002246054,0.005009789,0.000373373],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9643717,0.00005659755,0.03460813,0.00009945429,0.0004053368,0.0003737859,0.00001325246,0.00004521616,0.0000265331],"genre_scores_gemma":[0.9990627,0.00001602994,0.0005511315,0.00005335307,0.0001676784,0.00003360015,0.00004018892,0.00002280445,0.0000525174],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08863494,"threshold_uncertainty_score":0.4278971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00620620475476244,"score_gpt":0.2264343803135565,"score_spread":0.2202281755587941,"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."}}