{"id":"W1972154388","doi":"10.1118/1.2912177","title":"Optimization of exposure parameters in full field digital mammography","year":2008,"lang":"en","type":"article","venue":"Medical Physics","topic":"Digital Radiography and Breast Imaging","field":"Medicine","cited_by":87,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sunnybrook Health Science Centre","funders":"National Cancer Institute","keywords":"Digital mammography; Automatic exposure control; Imaging phantom; Mammography; Computer science; Dosimetry; Filter (signal processing); Nuclear medicine; Medical physics; Artificial intelligence; Computer vision; Medicine; 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":[0.001768155,0.0005387939,0.0003600576,0.0007245941,0.0002133989,0.0008716418,0.0005432581,0.0005328514,0.001092629],"category_scores_gemma":[0.008139182,0.0004275946,0.0003158272,0.0006995834,0.0002455569,0.0008487978,0.0008508693,0.000310153,0.0002702402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004781885,"about_ca_system_score_gemma":0.0002835293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003175282,"about_ca_topic_score_gemma":0.0003743958,"domain_scores_codex":[0.9986228,0.0005189234,0.0001373697,0.0002367519,0.0004309537,0.00005322468],"domain_scores_gemma":[0.9962031,0.002761258,0.0004136635,0.0002516252,0.00032269,0.0000477403],"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":[0.001512059,0.0002035283,0.007643414,0.0006764883,0.00009136364,0.0001207067,0.0002966648,0.01343671,0.8465825,0.0003919499,0.0003154748,0.1287291],"study_design_scores_gemma":[0.0001314634,0.003289472,0.06861886,0.0001206162,0.0002342246,0.001975779,0.0002115202,0.02105142,0.8960815,0.0007755082,0.007356775,0.0001527653],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8589935,0.004366871,0.1333919,0.0001886254,0.00003039922,0.0001784561,0.0002308588,0.0006055112,0.002013936],"genre_scores_gemma":[0.8743067,0.001790939,0.1220564,0.0001628751,0.00002051824,0.0001132136,0.0002841576,0.0003147016,0.0009504746],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001768155,"threshold_uncertainty_score":0.009351015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01150634475151125,"score_gpt":0.2292291287683771,"score_spread":0.2177227840168659,"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."}}