{"id":"W4249004135","doi":"10.1007/978-3-540-78450-0_2","title":"Detectors for Digital Mammography","year":2010,"lang":"en","type":"book-chapter","venue":"Medical radiology","topic":"Digital Radiography and Breast Imaging","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Toronto; Health Sciences Centre","funders":"","keywords":"Detector; SIGNAL (programming language); Computer science; Optics; Noise (video); Image resolution; Digital mammography; Physics; Electronic engineering; Computer vision; Mammography; Engineering; Image (mathematics)","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":[0.0003820232,0.001260136,0.0005496403,0.001663476,0.0008092873,0.002339271,0.001293037,0.001866692,0.05126407],"category_scores_gemma":[0.0007612032,0.000602647,0.0004773403,0.001178435,0.001160648,0.003319268,0.001429233,0.002991581,0.0316691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001214272,"about_ca_system_score_gemma":0.000996088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007876471,"about_ca_topic_score_gemma":0.002225915,"domain_scores_codex":[0.9996721,0.00004581207,0.000009786956,0.00006502074,0.0001868481,0.00002048747],"domain_scores_gemma":[0.9997943,0.00008052594,0.000008412188,0.00003091393,0.00007270314,0.00001308321],"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":[0.00002442613,0.00004892408,0.00008898218,0.0004059747,0.00001116566,0.0001344116,0.0002434645,0.0008003575,0.004211003,0.2937605,0.2538719,0.4463988],"study_design_scores_gemma":[0.000001873444,0.000007544526,0.00006072749,0.00009459324,0.000004196547,0.0002989055,0.00002653491,0.0003442606,0.000961952,0.02643248,0.9717591,0.000008004557],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0007120886,0.05232137,0.0603929,0.002434181,0.003239476,0.00008009194,0.0002100025,0.0008349823,0.8797748],"genre_scores_gemma":[0.00433416,0.02261422,0.01874433,0.00136528,0.0005509854,0.00004093976,0.0001730546,0.0002444505,0.9519326],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05126407,"threshold_uncertainty_score":0.1714954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009038338604521492,"score_gpt":0.2460279327659801,"score_spread":0.2369895941614586,"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."}}