{"id":"W4385276248","doi":"10.1302/1358-992x.2023.8.040","title":"AUTOMATIC SEGMENTATION AND BONE ARCHITECTURE ANALYSIS OF SUBCHONDRAL BONE IN THE MURINE PROXIMAL TIBIA: EVALUATION OF AN OPEN-SOURCE PIPELINE","year":2023,"lang":"en","type":"article","venue":"Orthopaedic Proceedings","topic":"Osteoarthritis Treatment and Mechanisms","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Sunnybrook Hospital","funders":"","keywords":"Segmentation; Pipeline (software); Subchondral bone; Tibia; Volume (thermodynamics); Biomedical engineering; X-ray microtomography; Trabecular bone; Computer science; Anatomy; Artificial intelligence; Medicine; Osteoporosis; Osteoarthritis; Pathology; Radiology; Physics","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":[0.002630597,0.001328451,0.0008151178,0.001416557,0.0005791581,0.001540244,0.001788063,0.001257138,0.003849003],"category_scores_gemma":[0.00303044,0.0006955217,0.001155068,0.0008108368,0.0004225673,0.0009520584,0.001109751,0.0008267325,0.002330713],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001278603,"about_ca_system_score_gemma":0.00180429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01040042,"about_ca_topic_score_gemma":0.01804234,"domain_scores_codex":[0.9989304,0.0001270056,0.00006772482,0.0004114201,0.000350209,0.0001131699],"domain_scores_gemma":[0.9989748,0.0003265649,0.0001170498,0.0001406502,0.0003724018,0.00006851827],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002544955,0.0006122766,0.01816863,0.001093999,0.0005685471,0.0004051321,0.00053243,0.0819525,0.2165484,0.002159445,0.01753467,0.6578789],"study_design_scores_gemma":[0.000143754,0.0006874649,0.02340597,0.0001334693,0.000213851,0.0006620857,0.0001901207,0.8259125,0.1313373,0.001926392,0.01527737,0.000109727],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2933027,0.001745776,0.5976481,0.0004021032,0.0002909573,0.0007735154,0.00694677,0.0934601,0.005429931],"genre_scores_gemma":[0.3404139,0.0006833882,0.6312451,0.0003187402,0.00004264204,0.000658119,0.01510967,0.004146181,0.007382208],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01040042,"threshold_uncertainty_score":0.02067977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02441258129307246,"score_gpt":0.3069423099223011,"score_spread":0.2825297286292286,"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."}}