{"id":"W1969390199","doi":"10.1080/10255842.2010.493512","title":"A depth-dependent model of the pericellular microenvironment of chondrocytes in articular cartilage","year":2010,"lang":"en","type":"article","venue":"Computer Methods in Biomechanics & Biomedical Engineering","topic":"Osteoarthritis Treatment and Mechanisms","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Chondrocyte; Extracellular matrix; Cartilage; Matrix (chemical analysis); Biophysics; In situ; Chemistry; Articular cartilage; Stiffness; Spheroid; Deformation (meteorology); Bone matrix; Cell biology; Anatomy; Materials science; Biomedical engineering; In vitro; Osteoarthritis; Composite material; Biology; Pathology; Biochemistry; Medicine","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":[0.0007152587,0.0002170653,0.0005072911,0.0003535994,0.00001487575,0.000005800948,0.0002416517,0.000220166,0.0000182702],"category_scores_gemma":[0.00006667637,0.0001677392,0.0001636756,0.0004833702,0.0000785891,0.00003758253,0.0002445737,0.000397773,0.00000129808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007649993,"about_ca_system_score_gemma":0.00005570839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001003369,"about_ca_topic_score_gemma":0.000007293605,"domain_scores_codex":[0.9983222,0.00006232809,0.0006054816,0.0003130152,0.0003597141,0.0003372302],"domain_scores_gemma":[0.9991667,0.00008240423,0.0001045953,0.0004790495,0.000023033,0.0001442736],"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":[0.00002084494,0.0003051657,0.00005677021,0.0001289137,0.00001425146,0.00003050309,0.0002537633,0.0004206782,0.973404,0.0005310622,0.000001148478,0.02483285],"study_design_scores_gemma":[0.001303493,0.000197028,0.00009220799,0.0001825722,0.00003087585,0.00002830055,0.00001543386,0.349135,0.6486261,0.0001812109,0.000110749,0.00009702356],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5495316,0.0002763932,0.4491753,0.00007838121,0.0005621345,0.0003445637,0.000005940528,0.00001921086,0.000006533076],"genre_scores_gemma":[0.6279068,0.00002550571,0.3719398,0.00002885311,0.00003726206,0.00002314813,0.000004938556,0.0000219107,0.00001176024],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3487143,"threshold_uncertainty_score":0.6840204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01298557157069315,"score_gpt":0.2686420243518832,"score_spread":0.2556564527811901,"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."}}