{"id":"W2009262994","doi":"10.1088/0031-9155/51/7/009","title":"Computation of mass-density images from x-ray refraction-angle images","year":2006,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Advanced X-ray Imaging Techniques","field":"Physics and Astronomy","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"National Institute of Arthritis and Musculoskeletal and Skin Diseases; Basic Energy Sciences; National Cancer Institute; National Institutes of Health","keywords":"Computation; Noise (video); Mammography; Refraction; Computer science; Density estimation; Artificial intelligence; Image (mathematics); Optics; Computer vision; Mathematics; Physics; Algorithm; Statistics; Medicine","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":[0.0009389629,0.000678038,0.0005736407,0.00170035,0.000278076,0.001190829,0.0007943496,0.000576554,0.001711237],"category_scores_gemma":[0.006875099,0.000549159,0.0004718065,0.0006543557,0.0004828141,0.001514261,0.0007349197,0.0005521273,0.0005464676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00056136,"about_ca_system_score_gemma":0.0005818798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001368434,"about_ca_topic_score_gemma":0.001698348,"domain_scores_codex":[0.9996995,0.00005715644,0.00002075009,0.0000385592,0.0001610857,0.00002293616],"domain_scores_gemma":[0.9987476,0.0006574205,0.0001838629,0.0001246422,0.0002380597,0.00004846366],"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":[0.0006456774,0.0001316502,0.009914548,0.0007470133,0.0001294538,0.0005249892,0.0005351055,0.2789688,0.3136289,0.03791355,0.001676528,0.3551838],"study_design_scores_gemma":[0.00002784316,0.00007461313,0.005116733,0.00003314056,0.00002660119,0.0003839607,0.0000611813,0.9020911,0.0822794,0.007206535,0.002644067,0.00005489594],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0327015,0.0001902498,0.9652278,0.00007776188,0.00002120314,0.00004712581,0.00007752376,0.0007473658,0.0009093879],"genre_scores_gemma":[0.2362019,0.0004401091,0.7618293,0.00004852364,0.00002759104,0.00006010729,0.0002602256,0.0002532405,0.0008789444],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001711237,"threshold_uncertainty_score":0.005724728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06027612362210166,"score_gpt":0.3720907531090819,"score_spread":0.3118146294869802,"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."}}