{"id":"W2091850050","doi":"10.1118/1.3002411","title":"Noise power properties of a cone‐beam CT system for breast cancer detection","year":2008,"lang":"en","type":"article","venue":"Medical Physics","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Institute of Biomedical Imaging and Bioengineering","keywords":"Breast cancer; Cone beam ct; Noise (video); Cone beam computed tomography; Medical physics; Medical imaging; Beam (structure); Optics; Cancer detection; Mammography; Cancer; Physics; Medicine; Nuclear medicine; Computed tomography; Radiology; Computer science; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001306791,0.00009852356,0.0002810855,0.00002114079,0.00007502748,0.000002442763,0.0000905312,0.00005251405,0.00005783301],"category_scores_gemma":[0.00008591597,0.00006935762,0.0001007451,0.0001382959,0.0002887109,0.00003238248,0.00002669073,0.0001674656,0.000006850091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006181528,"about_ca_system_score_gemma":0.0002066719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001294706,"about_ca_topic_score_gemma":0.000001445955,"domain_scores_codex":[0.9989562,0.00001032058,0.0002516634,0.0001676207,0.0004496835,0.0001644966],"domain_scores_gemma":[0.9992852,0.00003026686,0.00007919782,0.0002164273,0.0001765251,0.0002124243],"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":[0.0009986337,0.003304785,0.007342438,0.006652926,0.0005057593,0.0001165918,0.001155728,0.000005859494,0.697544,0.002619501,0.05049311,0.2292606],"study_design_scores_gemma":[0.002194249,0.000223537,0.002490556,0.001820675,0.0001806679,0.0006967374,0.00008688337,0.004026987,0.9807721,0.0001527645,0.00712561,0.000229278],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8857051,0.0002315891,0.1054964,0.006197376,0.0002234824,0.001170885,0.00007069232,0.0003523974,0.000552058],"genre_scores_gemma":[0.9983889,0.00005319508,0.0002861274,0.0004323735,0.0003417514,0.0003391587,0.00000575242,0.000020011,0.0001327063],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.283228,"threshold_uncertainty_score":0.2828322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02828767463130349,"score_gpt":0.2880387966732515,"score_spread":0.259751122041948,"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."}}