{"id":"W6906336776","doi":"10.17632/k5hdc9cz7w","title":"Integration of Swin UNETR and statistical shape modeling for a semi-automated segmentation of the knee and biomechanical modeling of articular cartilage","year":2023,"lang":"en","type":"dataset","venue":"Mendeley Data","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Calgary","funders":"","keywords":"Segmentation; Image segmentation; Osteoarthritis; Statistical model; Pattern recognition (psychology); Knee Joint; Joint (building); Magnetic resonance imaging","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001464158,0.0003403231,0.0007243182,0.0003032385,0.00007347664,0.00003869137,0.0005615099,0.0002710931,0.000008728846],"category_scores_gemma":[0.001062353,0.0002715002,0.00005318757,0.0004752087,0.0001332584,0.0002639969,0.0009576001,0.0002291535,0.000005744453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006497752,"about_ca_system_score_gemma":0.0001479999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009209656,"about_ca_topic_score_gemma":0.0005247737,"domain_scores_codex":[0.9968846,0.0002282066,0.001224183,0.0007162296,0.0006548615,0.0002918982],"domain_scores_gemma":[0.997399,0.0003057882,0.0005738883,0.001371004,0.0002650402,0.00008531037],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006780478,0.0003306401,0.000003233708,0.003366664,0.0004937601,0.00000548756,0.0002403987,0.04746707,0.4707683,0.0002300136,0.4753128,0.001103565],"study_design_scores_gemma":[0.0009175894,0.0001405844,0.000001482803,0.0005785024,0.0007759065,0.000004981744,0.0003965122,0.9918258,0.004513936,0.0004426466,0.0001849679,0.0002170639],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01359057,0.0001422753,0.1137953,0.00001561383,0.00008080313,0.001005766,0.87131,0.0000593834,3.586601e-7],"genre_scores_gemma":[0.1084327,0.0001065271,0.004808816,0.000007949601,0.00002262763,0.00005214973,0.8864979,0.00007026584,0.000001044452],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9443588,"threshold_uncertainty_score":0.9999737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09376215351515425,"score_gpt":0.3483936621763755,"score_spread":0.2546315086612213,"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."}}