{"id":"W2163683133","doi":"10.1016/j.clinbiomech.2011.06.009","title":"Predicting subchondral bone stiffness using a depth-specific CT topographic mapping technique in normal and osteoarthritic proximal tibiae","year":2011,"lang":"en","type":"article","venue":"Clinical Biomechanics","topic":"Osteoarthritis Treatment and Mechanisms","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Health Canada; Canadian Arthritis Network; Michael Smith Health Research BC","keywords":"Subchondral bone; Osteoarthritis; Cartilage; Stiffness; Medicine; Bone density; Anatomy; Biomedical engineering; Orthodontics; Articular cartilage; Materials science; Pathology; Osteoporosis; Composite material","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009831659,0.000362314,0.0007762996,0.0005277821,0.0001408916,0.00003907249,0.0001302317,0.0003199337,0.000055725],"category_scores_gemma":[0.0001889854,0.000350844,0.0002339207,0.000734042,0.000192866,0.0002331353,0.0001865976,0.0006134537,0.00001422367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006773622,"about_ca_system_score_gemma":0.0001340212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000314533,"about_ca_topic_score_gemma":0.0001175831,"domain_scores_codex":[0.9969801,0.0001500073,0.001129432,0.0007642308,0.0002929589,0.0006832211],"domain_scores_gemma":[0.9986885,0.0001620546,0.000223667,0.0004478731,0.0001006048,0.00037736],"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":[0.001589834,0.002121225,0.1886164,0.0004945674,0.0000809941,0.00459668,0.0007886151,1.838723e-7,0.5192887,0.002728439,0.00001679596,0.2796776],"study_design_scores_gemma":[0.1274657,0.05493387,0.09377144,0.02229095,0.002127055,0.0247015,0.009335024,0.009190485,0.6224031,0.01962143,0.006111389,0.00804799],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941618,0.001310344,0.001699277,0.00004657569,0.0006237422,0.001629044,0.00001783499,0.0001980123,0.0003133213],"genre_scores_gemma":[0.9833744,0.0003796364,0.01564777,0.0001226547,0.0002191851,0.0001009285,0.00003471398,0.00006476205,0.00005596631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2716296,"threshold_uncertainty_score":0.9998944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08179275045692198,"score_gpt":0.3090307549752858,"score_spread":0.2272380045183638,"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."}}