{"id":"W4412571314","doi":"10.1016/j.jocd.2025.101620","title":"Assessing the effect of DXA scanner drift on misclassification of bone density change: The Manitoba BMD registry","year":2025,"lang":"en","type":"article","venue":"Journal of Clinical Densitometry","topic":"Bone health and osteoporosis research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"CancerCare Manitoba; University of Winnipeg; University of Manitoba","funders":"Manitoba Centre for Health Policy, University of Manitoba; University of Manitoba","keywords":"Medicine; Scanner; Bone mineral; Demography; Gerontology; Internal medicine; Artificial intelligence; Osteoporosis","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.01880543,0.0008202865,0.0012046,0.002814301,0.001773322,0.001696113,0.004418422,0.001397235,0.0007523467],"category_scores_gemma":[0.05189882,0.001385099,0.001071774,0.00680101,0.001179254,0.001050954,0.001992406,0.001345012,0.0003249739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004804189,"about_ca_system_score_gemma":0.009627098,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6912681,"about_ca_topic_score_gemma":0.7104415,"domain_scores_codex":[0.9831434,0.009133295,0.001475323,0.001801384,0.003303936,0.001142611],"domain_scores_gemma":[0.9532942,0.01103243,0.01465031,0.007265487,0.01243735,0.001320224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001077442,0.00001489046,0.9981673,0.000009156844,0.0001292852,0.00003089454,0.0001599769,0.0001111573,0.00005730761,0.0000412434,0.0002386923,0.0009323024],"study_design_scores_gemma":[0.00002461739,0.00007385892,0.996614,0.00002825894,0.0002626449,0.0001404832,0.0003746927,0.001504335,0.0002717425,0.00005152536,0.0006404792,0.00001335637],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933997,0.000672769,0.001347106,0.0004242356,0.00004292857,0.0001090498,0.0029845,0.00003986847,0.000979708],"genre_scores_gemma":[0.9942801,0.0003068204,0.001853332,0.0003648848,0.00002620244,0.0001106106,0.002239584,0.00003555148,0.0007830207],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3087319,"threshold_uncertainty_score":0.6211002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1211560981375846,"score_gpt":0.5019035600500803,"score_spread":0.3807474619124957,"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."}}