{"id":"W2036714268","doi":"10.1118/1.1405842","title":"Parallel cascades: New ways to describe noise transfer in medical imaging systems","year":2001,"lang":"en","type":"article","venue":"Medical Physics","topic":"Digital Radiography and Breast Imaging","field":"Medicine","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"London Health Sciences Centre; Western University; Robarts Clinical Trials","funders":"","keywords":"Noise (video); Spectral density; Cascade; Computer science; Generalization; Covariance; Expression (computer science); Statistical physics; Optics; Physics; Algorithm; Image (mathematics); Artificial intelligence; Mathematics; Mathematical analysis; Chemistry; Telecommunications; Statistics","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":[0.001954844,0.001600752,0.000716756,0.001451814,0.0004883582,0.001505087,0.001831428,0.001671232,0.003318669],"category_scores_gemma":[0.003474522,0.0006056022,0.001181076,0.0008772827,0.001792964,0.003786889,0.001512505,0.00185364,0.001099898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001053574,"about_ca_system_score_gemma":0.0006539234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001186781,"about_ca_topic_score_gemma":0.0007010945,"domain_scores_codex":[0.9987904,0.0003635093,0.00005711084,0.0001439118,0.0005505483,0.00009441469],"domain_scores_gemma":[0.9990484,0.0004824431,0.0001020622,0.0001476823,0.0001797582,0.0000396883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006235899,0.00007560263,0.0005079345,0.0001437269,0.00005617989,0.0005388578,0.0003609713,0.2092446,0.01453149,0.7506983,0.001745833,0.02203409],"study_design_scores_gemma":[0.0000143372,0.00004778898,0.0001624904,0.00001701942,0.00001702865,0.0002695396,0.00003403054,0.7659795,0.002123074,0.2280399,0.003266111,0.00002919032],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007652851,0.0005654627,0.9851247,0.0001881055,0.00005724346,0.00008128645,0.00003910103,0.0001790009,0.006112276],"genre_scores_gemma":[0.586498,0.003165256,0.3879789,0.0008036549,0.0004801269,0.0007102041,0.0001510946,0.0004476361,0.01976523],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003318669,"threshold_uncertainty_score":0.01110202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02269945690133769,"score_gpt":0.2708465112599336,"score_spread":0.248147054358596,"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."}}