{"id":"W1968336458","doi":"10.1118/1.1538233","title":"Imaging performance of amorphous selenium based flat-panel detectors for digital mammography: Characterization of a small area prototype detector","year":2003,"lang":"en","type":"article","venue":"Medical Physics","topic":"Digital Radiography and Breast Imaging","field":"Medicine","cited_by":135,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"U.S. Army; Breast Cancer Research Foundation","keywords":"Detector; Detective quantum efficiency; Flat panel detector; Optics; Optical transfer function; Nyquist frequency; Digital radiography; Physics; Digital mammography; Spatial frequency; Noise power; Aliasing; Image resolution; Materials science; Mammography; Image quality; Computer science; Power (physics); Telecommunications; Bandwidth (computing); Radiography","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":[0.0001666352,0.0001995035,0.0004030663,0.0001473973,0.00003863982,0.00001889123,0.0001194682,0.00006662914,0.00002269297],"category_scores_gemma":[0.0001971966,0.0001714096,0.0002828813,0.0005787372,0.0002422167,0.0002192524,0.00001484499,0.000158827,0.000001324701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001802419,"about_ca_system_score_gemma":0.0002116588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003590166,"about_ca_topic_score_gemma":3.739255e-7,"domain_scores_codex":[0.9985641,0.00001534168,0.0004004033,0.0002427783,0.0004717398,0.0003056282],"domain_scores_gemma":[0.9990481,0.00008924778,0.0002001911,0.0002325609,0.000222035,0.0002078677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001620243,0.001077455,0.5421519,0.002867019,0.0002147202,0.00001628339,0.0001555261,0.000007729735,0.1123092,0.000086673,0.00001953413,0.3394738],"study_design_scores_gemma":[0.00495224,0.001768611,0.07064086,0.001534373,0.0002740236,0.00008454024,0.00003181929,0.01731077,0.9016123,0.0003048034,0.0009660764,0.0005195137],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9589673,0.00002497036,0.03947532,0.00005058538,0.0001071381,0.0008351452,0.00007363054,0.00006101147,0.0004049102],"genre_scores_gemma":[0.9991055,0.000004482733,0.0004434573,0.0001125065,0.00008878882,0.00008177353,0.0001134654,0.00003742586,0.00001265739],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7893031,"threshold_uncertainty_score":0.698988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01505679589000007,"score_gpt":0.2166852499539185,"score_spread":0.2016284540639184,"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."}}