{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.009503402,0.000144727,0.001028526,0.0003376211,0.0001406244,0.00003518021,0.0002690937,0.0002798684,0.0000126426],"category_scores_gemma":[0.0113203,0.00006925316,0.0005246297,0.0008860503,0.000441823,0.00009961589,0.00008252267,0.001595235,0.00000576668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000669642,"about_ca_system_score_gemma":0.0004412053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008442281,"about_ca_topic_score_gemma":0.00002216289,"domain_scores_codex":[0.995569,0.001070948,0.001867698,0.0001866134,0.00105164,0.0002541142],"domain_scores_gemma":[0.9903476,0.006360557,0.001548717,0.000666544,0.0008721244,0.0002045107],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003589717,0.0004587566,0.8542074,0.0009444699,0.0002780661,0.00008944799,0.00005463373,0.00000201773,0.0059201,0.00007362594,0.0127525,0.1216293],"study_design_scores_gemma":[0.002039721,0.001559621,0.9793031,0.00122022,0.0002928102,0.0001106874,0.0003384928,0.000122041,0.01315634,0.00004686901,0.001760122,0.0000499627],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9817237,0.001381449,0.00006724133,0.01456515,0.001048579,0.0004189166,0.00000191453,0.000005959542,0.0007871253],"genre_scores_gemma":[0.9970604,0.0004719245,0.0001502796,0.001180559,0.0009215181,0.000003842902,0.000001727059,0.00001249875,0.0001972654],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1250957,"threshold_uncertainty_score":0.9970078,"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."}}