{"id":"W4392757193","doi":"10.1093/jbmr/zjae039","title":"Transferability of bone phenotyping and fracture risk assessment by μFRAC from first-generation high-resolution peripheral quantitative computed tomography to second-generation scan data","year":2024,"lang":"en","type":"article","venue":"Journal of Bone and Mineral Research","topic":"Bone health and osteoporosis research","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Children's Hospital; Alberta Bone and Joint Health Institute; University of Calgary","funders":"","keywords":"Quantitative computed tomography; Reproducibility; Nuclear medicine; Scanner; Transferability; Computed tomography; Pearson product-moment correlation coefficient; Medicine; Correlation coefficient; Cohort; Bone density; Mathematics; Radiology; Biomedical engineering; Computer science; Statistics; Osteoporosis; Internal medicine; Artificial intelligence","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":[0.01332261,0.0009349078,0.0006646098,0.001225797,0.0003545954,0.001639348,0.001231687,0.0008419429,0.000875935],"category_scores_gemma":[0.03587895,0.0005589544,0.001306963,0.0006148653,0.0007769087,0.000679576,0.001427028,0.0009364818,0.0004220045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009316084,"about_ca_system_score_gemma":0.001106229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0127867,"about_ca_topic_score_gemma":0.01092968,"domain_scores_codex":[0.9962503,0.001551598,0.0001609624,0.001191916,0.0006844293,0.0001608482],"domain_scores_gemma":[0.9860196,0.00749897,0.001440844,0.003405679,0.001421002,0.0002139792],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007051511,0.0002748097,0.7020059,0.0001457781,0.001233602,0.0003157208,0.0006276846,0.1665615,0.0122168,0.0007111168,0.0009862254,0.1142156],"study_design_scores_gemma":[0.00005111872,0.0005761401,0.317804,0.00006453659,0.000311428,0.000681373,0.0001759863,0.6676607,0.009329398,0.002262519,0.0009921172,0.00009078234],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8956299,0.0003158497,0.1009522,0.00022345,0.00003601065,0.0001563553,0.0008652863,0.0007744997,0.001046473],"genre_scores_gemma":[0.9844002,0.00006936245,0.01451772,0.00005948839,0.000009894122,0.00005623671,0.0006458975,0.00004530298,0.0001961151],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01332261,"threshold_uncertainty_score":0.07045752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09394777183265174,"score_gpt":0.4098670492798669,"score_spread":0.3159192774472152,"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."}}