{"id":"W2015379277","doi":"10.1117/12.658076","title":"&lt;title&gt;Progress in multiple-image radiography&lt;/title&gt;","year":2006,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced X-ray Imaging Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Radiography; Mammography; Refraction; Medical imaging; Conventional radiography; Medical physics; Focus (optics); Computer science; Computed radiography; Artificial intelligence; Optics; Nuclear medicine; Computer vision; Physics; Medicine; Image quality; Radiology; 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":[0.002758677,0.0006779229,0.0007761846,0.00261208,0.0005240449,0.003107202,0.00151375,0.001526794,0.05725714],"category_scores_gemma":[0.002671153,0.0003617097,0.0004661744,0.003035475,0.001067583,0.004369162,0.001144881,0.002097541,0.03855859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009853537,"about_ca_system_score_gemma":0.0009230684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009534413,"about_ca_topic_score_gemma":0.001174657,"domain_scores_codex":[0.9989453,0.000149094,0.00005877695,0.0001796344,0.0005998288,0.00006733742],"domain_scores_gemma":[0.9966169,0.0009406644,0.0001786279,0.0003186213,0.001738048,0.0002071035],"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":[0.0001435589,0.0001389477,0.0005222629,0.001444631,0.00001561059,0.0002322672,0.0001397325,0.0009677067,0.02502454,0.02728055,0.08350057,0.8605896],"study_design_scores_gemma":[0.00001869612,0.0001895809,0.001089378,0.0002906864,0.00001902557,0.001064659,0.00007766225,0.002793476,0.02453453,0.005397426,0.9644784,0.00004641168],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.01259205,0.3963349,0.2347539,0.02054117,0.01550937,0.0003377074,0.0006529488,0.004900898,0.3143772],"genre_scores_gemma":[0.07148942,0.3585072,0.2156734,0.003602607,0.01293496,0.0001715829,0.001827697,0.002462183,0.3333309],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05725714,"threshold_uncertainty_score":0.1915442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006852718773549993,"score_gpt":0.2313675952493832,"score_spread":0.2245148764758332,"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."}}