{"id":"W2031628593","doi":"10.1118/1.4801905","title":"Anatomical noise in contrast‐enhanced digital mammography. Part I. Single‐energy imaging","year":2013,"lang":"en","type":"article","venue":"Medical Physics","topic":"Digital Radiography and Breast Imaging","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; Ontario Tech University; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Mammography; Digital mammography; Medical imaging; Contrast (vision); Noise (video); Medical physics; Energy (signal processing); Contrast-to-noise ratio; Physics; Computer science; Medicine; Optics; Radiology; Computer vision; Image quality; Breast cancer; 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":[0.0020361,0.0005836575,0.0004373042,0.001673906,0.0002421365,0.0008533152,0.0004935457,0.0008489532,0.0006051671],"category_scores_gemma":[0.01375998,0.0003733585,0.0003512197,0.000829705,0.000862462,0.0007184576,0.0005821461,0.0002548788,0.0003019871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003951512,"about_ca_system_score_gemma":0.0001546474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006202659,"about_ca_topic_score_gemma":0.000625285,"domain_scores_codex":[0.998558,0.0004402563,0.0001016927,0.000192017,0.0006587201,0.00004934289],"domain_scores_gemma":[0.9929126,0.005257406,0.0008374427,0.0003249961,0.0005774499,0.00009005771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004024791,0.0003963653,0.2347811,0.001975439,0.0003441527,0.00480364,0.001175612,0.01382932,0.2988726,0.001581639,0.0008060283,0.4374094],"study_design_scores_gemma":[0.0001014168,0.004464984,0.6405841,0.0003934406,0.0007908312,0.05375034,0.0005974761,0.0576472,0.2276154,0.002991325,0.01090061,0.0001630023],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.919431,0.01161707,0.06708938,0.0001457476,0.00005494231,0.0001055479,0.00008329115,0.0001684252,0.001304646],"genre_scores_gemma":[0.980227,0.002289343,0.01646329,0.00008668457,0.00006420728,0.0000468027,0.00017949,0.00005956352,0.0005837195],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0020361,"threshold_uncertainty_score":0.01076806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006298797560840437,"score_gpt":0.2180681929858994,"score_spread":0.211769395425059,"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."}}