{"id":"W4412196595","doi":"10.1016/j.clinimag.2025.110541","title":"Corrigendum to “Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review” [Clin Imaging 118 (2025) 110369]","year":2025,"lang":"en","type":"erratum","venue":"Clinical Imaging","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"SickKids Foundation","funders":"","keywords":"Traceability; Medicine; Mammography; Diversity (politics); Medical physics; Software engineering; Internal medicine; Engineering; Anthropology","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0209494,0.002293363,0.005057611,0.009719164,0.002491046,0.005310787,0.003508815,0.006580841,0.1176772],"category_scores_gemma":[0.2389322,0.001925716,0.004530728,0.008648694,0.00298666,0.002732863,0.004174781,0.006574345,0.03457574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007744404,"about_ca_system_score_gemma":0.02039304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06229154,"about_ca_topic_score_gemma":0.1433092,"domain_scores_codex":[0.9779258,0.006796606,0.005659885,0.001747432,0.006867016,0.001003308],"domain_scores_gemma":[0.8521178,0.05056114,0.01389149,0.00531782,0.07502595,0.003085798],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"systematic_review","study_design_scores_codex":[0.00002524531,0.000003232987,0.00006332884,0.001732084,0.00005601505,0.00005980288,0.00001710203,0.00001359645,0.000009310828,0.0001595932,0.9942423,0.003618539],"study_design_scores_gemma":[0.0005810942,0.00006210146,0.003171596,0.02238311,0.001094133,0.0003897548,0.0001512672,0.0001789903,0.0001683586,0.002055486,0.9696315,0.0001325104],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.000123384,0.01808888,0.0006645615,0.190742,0.7736126,0.0004211818,0.01052704,0.0004093253,0.00541112],"genre_scores_gemma":[0.005832095,0.05453619,0.005090208,0.5753234,0.243132,0.002893225,0.01253526,0.0009364759,0.09972125],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9790506,"threshold_uncertainty_score":0.3936693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05418804972057811,"score_gpt":0.3956368612046027,"score_spread":0.3414488114840246,"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."}}