{"id":"W2559761027","doi":"10.1186/s40634-016-0072-2","title":"Quantitative Computed Tomography (QCT) derived Bone Mineral Density (BMD) in finite element studies: a review of the literature","year":2016,"lang":"en","type":"review","venue":"Journal of Experimental Orthopaedics","topic":"Bone health and osteoporosis research","field":"Medicine","cited_by":123,"is_retracted":false,"has_abstract":true,"ca_institutions":"St Joseph's Health Care; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Lawson Health Research Institute","keywords":"Quantitative computed tomography; Imaging phantom; Scanner; Bone mineral; Tomography; Finite element method; Bone density; Parametric statistics; Hounsfield scale; Computed tomography; Calibration; Biomedical engineering; Materials science; Computer science; Nuclear medicine; Mathematics; Medicine; Artificial intelligence; Radiology; Osteoporosis; Statistics; Engineering; Structural engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006987078,0.001470954,0.003266713,0.01252543,0.000477265,0.002642854,0.002423298,0.002003477,0.002719868],"category_scores_gemma":[0.01822131,0.0009350886,0.002286737,0.01321894,0.00155379,0.002380562,0.001250956,0.001298998,0.0008234576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001322267,"about_ca_system_score_gemma":0.004069881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003274746,"about_ca_topic_score_gemma":0.004812291,"domain_scores_codex":[0.9967591,0.0006650378,0.0010854,0.0004490982,0.0009614077,0.00007985859],"domain_scores_gemma":[0.9750302,0.01956622,0.002123716,0.0003129653,0.002810897,0.0001560255],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0001221098,0.00007845979,0.001871116,0.2456295,0.0006622013,0.0002688076,0.000355566,0.0007728999,0.0008642034,0.002029166,0.01082601,0.7365199],"study_design_scores_gemma":[0.00005815611,0.0003820611,0.01102609,0.3790171,0.006139779,0.004906698,0.000870846,0.0009220055,0.001700938,0.005005061,0.5897778,0.0001935796],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000160183,0.9991279,0.0002821691,0.000151788,0.00006325829,0.000009793969,0.00004069721,0.000005316607,0.0001588587],"genre_scores_gemma":[0.001497044,0.9973219,0.0007659525,0.0001728204,0.0001028934,0.00002521648,0.00005367545,0.000004193814,0.00005629158],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01252543,"threshold_uncertainty_score":0.03695166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07567807311112426,"score_gpt":0.4266902030341854,"score_spread":0.3510121299230611,"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."}}