{"id":"W1981268391","doi":"10.1118/1.3244112","title":"Poster — Wed Eve—08: Effectiveness RMI‐156 Mammography Accreditation Phantom in Evaluating Digital Mammography Systems","year":2009,"lang":"en","type":"article","venue":"Medical Physics","topic":"Digital Radiography and Breast Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency","funders":"","keywords":"Imaging phantom; Mammography; Digital mammography; Image quality; Pixel; Computer science; Medical physics; Medicine; Artificial intelligence; Nuclear medicine; Image (mathematics); Breast cancer","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":[0.003451054,0.0005302671,0.0002591714,0.0006112564,0.0003345681,0.001144569,0.0004364756,0.0008032118,0.03760031],"category_scores_gemma":[0.002729168,0.0002257538,0.0003310753,0.0002165833,0.0003347225,0.0004688277,0.0008021856,0.0004968335,0.008897737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005235778,"about_ca_system_score_gemma":0.0003232352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004089429,"about_ca_topic_score_gemma":0.0007612239,"domain_scores_codex":[0.9991928,0.0002050288,0.00005553765,0.000130421,0.0003429061,0.0000733276],"domain_scores_gemma":[0.9984118,0.0004037333,0.0001557745,0.000203346,0.000587019,0.0002383767],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.01462991,0.003033299,0.04932553,0.001447295,0.0001369166,0.0007623988,0.000744057,0.003212001,0.4727283,0.002810377,0.06088708,0.3902828],"study_design_scores_gemma":[0.0007184823,0.01591742,0.2277499,0.000323556,0.0002111097,0.003365797,0.0005498182,0.01208953,0.6470598,0.0008193533,0.09098059,0.0002146405],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7875103,0.001776867,0.02456101,0.001663039,0.001376295,0.001785489,0.002294337,0.001700335,0.1773323],"genre_scores_gemma":[0.8364629,0.0006659872,0.03508688,0.0005068269,0.0002855729,0.0003588855,0.002806391,0.0005397398,0.1232869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03760031,"threshold_uncertainty_score":0.1257856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01716446488542114,"score_gpt":0.3095015475546821,"score_spread":0.292337082669261,"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."}}