{"id":"W1996605531","doi":"10.1177/153303460400300401","title":"Detectors for Digital Mammography","year":2004,"lang":"en","type":"review","venue":"Technology in Cancer Research & Treatment","topic":"Digital Radiography and Breast Imaging","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Mammography; Digital radiography; Digital mammography; Fluoroscopy; Computer science; Detector; Medical physics; Radiography; Subtraction; Breast imaging; Flat panel detector; Computer vision; Image resolution; Dynamic range; Artificial intelligence; Medicine; Radiology; Telecommunications","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002160678,0.0005262073,0.001713515,0.00532243,0.0001088624,0.00008442987,0.0003592301,0.0005869335,0.00002323465],"category_scores_gemma":[0.00008034582,0.0003770311,0.0009194709,0.00387154,0.0007586281,0.0001173679,0.0001060542,0.000789684,0.00003423048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00266059,"about_ca_system_score_gemma":0.001495903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001839163,"about_ca_topic_score_gemma":0.00005997578,"domain_scores_codex":[0.9970925,0.00003116963,0.0005169214,0.0008358289,0.0004032377,0.001120353],"domain_scores_gemma":[0.9986205,0.0002219613,0.0001079974,0.0007214797,0.0001451514,0.0001829516],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006695374,0.0006352576,0.000512103,0.006325284,0.0006852281,0.0002928245,0.00001486108,2.581725e-7,6.139355e-7,0.0005289912,0.00007541349,0.9908622],"study_design_scores_gemma":[0.001852321,0.002322153,0.000016497,0.02495836,0.0004541651,0.0003300523,0.00005377104,4.550803e-7,0.00003869825,0.004390375,0.9652753,0.0003078504],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003401673,0.993021,0.000006876722,0.0007433083,0.00009365229,0.004235842,0.0004471912,0.0002619387,0.0008499936],"genre_scores_gemma":[0.003033981,0.9869897,0.0001752097,0.000006167801,0.00009464764,0.009061056,0.0001578878,0.000099422,0.0003819748],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9905543,"threshold_uncertainty_score":0.9998682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1498488972044751,"score_gpt":0.4940678459992623,"score_spread":0.3442189487947873,"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."}}